Composite Experimental Design Research Articles

Analytical quality-by-design guided development of a novel and robust HPTLC method for quantifying plumbagin from Plumbago species

The study utilizes an analytical quality-by-design (AQbD) approach to establish a robust and efficient HPTLC method for plumbagin quantification in plumbago species. The highest-risk critical method parameters (CMP; concentration of plumbago and composition of mobile phase) and most appropriate critical analytical attributes (CAA; Peak area and retention factor [Rf]) were employed in the AQbD methodology. These CMP were tuned for higher plumbagin recovery using the central composite design (CCD) experiment. The created approach was validated by the requirements outlined in the International Conference on Harmonization (ICH) Q2 (R2). Every plate involved in the proposed method validation has been subjected to the passing requirements of the system suitability test (SST). The low LOD (16.93 ng/mL) and LOQ (49.68 ng/mL) values and the minimal divergence in intra- and inter-day studies validate the developed method’s high precision and sensitivity. Further experiments employing the proposed method to determine the amount of plumbagin from the two distinct plant sources harvested under two different climate conditions determined the highest plumbagin content in P. indica, which is in line with the results. To summarize, the AQbD method may be used in other plant systems to optimize various factors and get a greater concentration of the desired plant metabolite.

Optimisation of Lactobacillus fermentation conditions and its application in the fermentation of salt-free sauerkraut.

To identify what are the dominant lactic acid bacteria (LAB) involved in the fermentation of salt-free sauerkraut, and optimize its industrial culture conditions, we isolated and identified a strain of LAB, which is referred to as Lactobacillus sp. DF_001, with the preservation number CCTCC NO: M20232593, from five different regions in Guizhou Province. Industrial culture conditions were optimized using Plackett-Burman and Central Composite design experiments, and the potential role of this LAB in salt-free sauerkraut fermentation was validated. Bioproduction was optimal with a culture time of 66 h, starch/water ratio of 1.7% and inoculum of 0.02%, which gave approximately three-fold higher yield than the basal culture medium DeMan-Rogosa-Sharpe medium (MRS). The LAB was used in small-scale industrial experiments. The Dafang LAB significantly enhanced the sensory score of the salt-free sauerkraut products by about 32% compared to the control group. The total acid content increased by about 32% and the sugar and nitrite contents were reduced by 67.27 and 69.58%, respectively. The total number of bacterial colonies decreased by 37.5%. All other indicators complied with the national standard, providing overall the basis to improve salt-free sauerkraut fermentation.

Multi-residue analysis of four aminoglycoside antibiotic pesticides in plant agricultural products

Simplified and effective pretreatment methods combined with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) for the determination of four aminoglycoside antibiotic pesticides kasugamycin, validamycin, streptomycin sulfate and zhongshengmycin in high starchy content matrix (rice), high water and high acidic content matrix (citrus) and high water content matrix (melon) were established. Single-factor and central composite design (CCD) experiments were employed to optimize the pretreatment conditions, resulting in the optimal factor combinations and achieving scientifically accurate outcomes. Validation results proved satisfactory, with all four target compounds exhibiting correlation coefficients (r) exceeding 0.99 within the linear range in three matrices. The recoveries were 81.5–102.2 %, and both inter-day and intra-day relative standard deviations (RSDs) were below 10.7 %. The limits of detection (LODs) were 0.1–4.0 μg/kg, with limits of quantitation (LOQs) consistently at 50 μg/kg. Furthermore, the methods were applied to potato, grape, and cucumber matrices to further validate their applicability.

Hydrodynamic cavitation assisted pretreatment of sugarcane bagasse in the presence of yeast cell mass for the production of sugars and their use for biopigments production by Monascus ruber

Hydrodynamic cavitation-assisted pretreatment of sugarcane bagasse tested in the, with the addition of yeast extract. This pretreatment was investigated using a 22 central composite design experiment. A total of 11 experiments were performed. The pretreated biomass was then tested for enzymatic hydrolysis for the sugars production. Various enzymatic loadings (15–20 FPU/g biomass) and concentrations of yeast extract (0.25–1 g/L) were studied during the enzymatic hydrolysis. Optimization of yeast extract insertion was performed to simultaneously facilitate the infusion of cellulolytic enzymes into the pores of the pre-treated bagasse concomitantly inhibiting enzyme absorption caused by residual lignin. The optimized results revealed an 81 % glucan hydrolysis yield and a 78 % xylan hydrolysis yield after the enzymatic hydrolysis under optimized conditions (20 FPU/g and 1 g/L of yeast extract). The hydrolysate rich in sugars derived from carbohydrate polymers and nitrogen sources derived from hydrolysis of yeast cream was assessed for biopigments production by Monascus ruber. The hydrolysate used for M. ruber fermentation showed the production of pigments with 15 AU (absorbance units) for yellow, 15 AU for orange and 20 AU for red after 9 days of fermentation. These results proved the efficiency of using yeast cream as a potential blocking agent of lignin in turn increasing the sugars production and a nitrogen source for the M. ruber for biopigments production from sugarcane bagasse hydrolysate.

Morphological characteristics of activated sludge recovered from biological reactors impact on the energy requirement for centrifugal dewatering

The effect of sludge dewatering on handling and transport costs as well as the impact of various parameters like sludge characteristics, the used dewatering equipment and the adopted specific operating conditions, on the efficiency of this step, were considered in the present study. The influence of a laboratory-scale centrifugation for dewatering activated sludge (AS) was also investigated. Additionally, models to describe the relationships between independent variables like centrifugation speed, AS volume and fixed time and dependent variables like the percentage of solid cake (% GS). The used approach was based on the response surface methodology (RSM) along with a central composite design experiment, considering three distinct types of AS: healthy (BS), partially bulking (BF), and deflocculated (BD) sludges. The morphological characteristics of the sludge do have an effect on the operating conditions for the centrifugation, hence the energy consumption for a desired dewatering level. For the case of BS sludge, a centrifugation at 2600 rpm for 10 min, using a 10.3 mL plug, led to a solid cake of 12.65 %, whereas for BD sludge, with a higher centrifugation at 3000 rpm for 17.30 min and a smaller plug volume (8 mL) led to 6.82 %, roughly half of the previous percentage.

Optimized phenol degradation and lipid production by Rhodosporidium toruloides using response surface methodology and genetic algorithm-optimized artificial neural network

Oleaginous yeast can produce lipids while degrading phenol in wastewater treatment. In this study, a Plackett-Burman Design (PBD) was adopted to identify key factors of phenol degradation and lipid production using R toruloides 9564T. While temperature, inoculum size, and agitation were significant for both the processes (p < 0.05), pH and incubation were significant for lipid production, and phenol removal, respectively. Results from four factors (pH, temperature, inoculum size, and incubation period) central composite design (CCD) experiment were used to formulate quadratic and genetic algorithm-optimized ANN models. The reduced quadratic model for phenol degradation (R2: 0.993) and lipid production (R2: 0.958) were marginally inferior to ANN models (R2: 0.999, 0.982, respectively) on training sets. Multi-objective optimization with equal importance suggests phenol degradation between 106.4 and 108.76%, and lipid production of 0.864–0.903 g/L, by polynomial and ANN models. Complete phenol degradation (100%) and 3.35-fold increment (0.918 g/L) in lipid production were obtained at pH 6.07, inoculum size 14.68% v/v, at 29.5 °C in 92.17 h experimentally.

Facilely Promoting the Concentration of Baicalin in Polylactic Acid Fiber for UV Shielding and Antibacterial Functions: A Customized and Sustainable Approach.

There is a significant trend towards the integration of natural substances with bio-polymers for fully bio-based functional composites. Polylactic acid is regarded as a promising biodegradable polymer for replacing synthetic polymers. Differing from the case of natural fiber, the incompatibility of polylactic acid with bio-based molecules prevents it from being used to fabricate high-quality sustainable composites. This work presents a simultaneous ultraviolet shielding and antibacterial finishing process of polylactic acid combined with bioactive baicalin and an eco-friendly ester, which is highlighted for (a) the lack of synthetic chemicals involved in such process, (b) adsorption enhancement achieved at a mild temperature, and (c) marginal color change on treated polylactic acid. A response surface methodology was adopted to analyze the impacts of various factors on the baicalin quantity in polylactic acid, and to optimize the treatment condition. The uptake ratio of baicalin in polylactic acid was drastically promoted from 8.5 mg/g to 21.1 mg/g using methyl cinnamate. The response surface methodology based on a central composite design experiment indicated that the usage of baicalin was the most significant factor followed by methyl cinnamate and temperature. After optimization, a very faint color depth of 1.2 was apparent, but UPF 50+ and 92% bacterial reduction could be achieved. In all, the success in strengthening of the functionalities of polylactic acid extends the applications of polylactic acid products.

Optimization of maltodextrin concentration and spray drying temperature on physicochemical characteristics of powdered edamame milk

Peeled edamame can be processed into a product that will increase added value, including edamame milk. The perishable nature of milk requires further processing, such as drying it into powder. One of the commonly used fillers is maltodextrin because it can improve the product’s physical properties. With this treatment process, the physicochemical characteristics could be changed. Therefore, this study aimed to optimize the treatment of the physicochemical characteristics of edamame milk powder. Response Surface Methodology (RSM) with Central Composite Design (CCD) experiment with maltodextrin concentration factor (5.71%-10.00%) and spray drying temperature (160°C-215°C) was used in this study. Analysis of physicochemical characteristics carried out included water content, water activity, solubility, hygroscopicity, and color (a(-)). The results showed that treatment with the combination of 6.00% maltodextrin and 215 °C of drying temperature offer the optimum condition in producing a high-quality edamame milk powder.

Sustainable appraisal of lipstick tree seeds (Bixa orellana)-based bixin natural orange colorant for green mordanted silk fabrics and wool yarns.

This research aims to optimize the silk and wool dyeing process using natural dyes from Bixa orellana (annatto) through response surface methodology. Central composite design experiments highlight the significant enhancement of color outcomes achieved through microwave treatment. For silk, the optimal conditions (80 °C for 40 min) with annatto extract yield a color strength (K/S) of 17.8588, while wool achieves a K/S of 7.5329. Introducing eco-friendly bio-mordants, such as pomegranate peel and red sumac tannins, enhances color strength. Pre-dyeing treatments with 2% red sumac, 1.5% pomegranate peel, and weld flower extracts for silk produce high color strength, with K/S values of 16.4063, 16.3784, and 12.1658, respectively. Post-dyeing, the K/S values increase to 40.1178, 17.4779, and 21.6494. Wool yarn exhibits similar improvements, with pre-dyeing K/S values of 13.1353, 13.5060, and 16.3232, escalating to 10.5892, 15.3141, and 23.4850 post-dyeing. Furthermore, this research underscores improved colorfastness properties, including notable enhancements in light, wash, and rubbing fastness for both silk fabric and wool yarn. These findings underscore the efficacy of the proposed sustainable dyeing methods, offering valuable insights for eco-friendly textile production.

Оптимизация параметров импульсной лазерной наплавки стали 30ХГСН2А с использованием генетического алгоритма

The paperpresents the optimization of pulsed laser cladding of structural steel using a genetic algo-rithm. Using the ANSYS Workbench software, finite element modelling of laser cladding on a 30ХГСН2А steel substrate with an additive in the form of wire was conducted, considering the temperature dependence of the material's thermophysical properties. A surrogate model for pulsed laser cladding of 30ХГСН2Аsteel was developed employing a face-centered version of the central composite design experiment. The time inter-vals corresponding to the end time of the three fronts of the laser pulse and the diameter of the filler wire were considered as variable factors. The maximum temperatures in the treatment zone were used as re-sponses. In order to optimize pulsed laser cladding of 30ХГСН2А steel, the maximum temperature limit val-ues in the treatment zone were established for three moments of time that corresponded to the laser pulse fronts at the three points in the finite element model. A comparison was made between the parameters ob-tained from optimization and those derived from finite element modelling. When determining temperatures, the maximum percentage error of the results obtained via the genetic algorithm did not exceed 3.5 %

Preparation of Compound Salvia miltiorrhiza-Blumea balsamifera Nanoemulsion Gel and Its Effect on Hypertrophic Scars in the Rabbit Ear Model.

Hypertrophic scars (HS) still remain an urgent challenge in the medical community. Traditional Chinese medicine (TCM) has unique advantages in the treatment of HS. However, due to the natural barrier of the skin, it is difficult for the natural active components of TCM to more effectively penetrate the skin and exert therapeutic effects. Therefore, the development of an efficient drug delivery system to facilitate enhanced transdermal absorption of TCM becomes imperative for its clinical application. In this study, we designed a compound Salvia miltiorrhiza-Blumea balsamifera nanoemulsion gel (CSB-NEG) and investigated its therapeutic effects on rabbit HS models. The prescription of CSB-NEG was optimized by single-factor, pseudoternary phase diagram, and central composite design experiments. The results showed that the average particle size and PDI of the optimized CSB-NE were 46.0 ± 0.2 nm and 0.222 ± 0.004, respectively, and the encapsulation efficiency of total phenolic acid was 93.37 ± 2.56%. CSB-NEG demonstrated excellent stability and skin permeation in vitro and displayed a significantly enhanced ability to inhibit scar formation compared to the CSB physical mixture in vivo. After 3 weeks of CSB-NEG treatment, the scar appeared to be flat, pink, and flexible. Furthermore, this treatment also resulted in a decrease in the levels of the collagen I/III ratio and TGF-β1 and Smad2 proteins while simultaneously promoting the growth and remodeling of microvessels. These findings suggest that CSB-NEG has the potential to effectively address the barrier properties of the skin and provide therapeutic benefits for HS, offering a new perspective for the prevention and treatment of HS.

Combined hydroxyphenyl-modified adhesive with the ion-pair strategy for long-lasting delivery of clonidine in single-layer matrix-type patch

Existing long-acting patches usually use controlled-release membranes to achieve constant rate delivery of the drug, which is complex and costly to prepare due to the 5-layer structure, so there is a necessity to develop a method to simplify the patch design and to control constant rate drug delivery. This study prepared a 7-day long-acting clonidine (CLO) patch using the ion-pair strategy based on hydroxyphenyl-modified pressure-sensitive adhesive (HP-PSA) and clarified the molecular mechanism of controlled delivery. Single factorial and central composite design (CCD) experiments were used to optimize the patch formulation, which was evaluated by a pharmacokinetic study. The controlled drug delivery mechanism was investigated by FTIR, 1H NMR, differential scanning calorimetry (DSC), confocal laser scanning microscopy (CLSM), molecular modeling, and rheology study. The optimized patch was formulated with 4.80% (w/w) CLO-AA (azelaic acid) as API and HP-PSA as PSA matrix and 95.00 μm thickness. The single-layer patch not only simplifies the preparation process but also has a zero-level skin penetration profile (r = 0.9592) in vitro. Compared with the commercial patch (AUC0-t = 7748.51 ± 662.76 h ng/ml, MRT0-t = 71.04 ± 9.30h), the pharmacokinetic behavior of the optimization group was semblable (AUC0-t = 8160.28 ± 694.04 h ng/ml, MRT0-t = 63.19 ± 12.38h). Mechanistic studies showed that ion-pair improved drug interaction with HP-PSA, leading to controlled drug release. Changes in drug physicochemical properties decreased skin permeability and increased drug-skin interaction, resulting in a constant delivery rate. In conclusion, the 7-day long-acting drug delivery of the CLO patch was achieved by the ion-pair strategy, which simplified the preparation process, and inspired a long-acting transdermal drug delivery system.

Optimizing the Antimicrobial Activity of Sodium Hypochlorite (NaClO) over Exposure Time for the Control of Salmonella spp. In Vitro.

Fish is a nutritionally rich product; however, it is easily contaminated by pathogenic microorganisms, such as Salmonella spp. Therefore, this study aimed to identify the best concentration of sodium hypochlorite (NaClO), exposure time, and water temperature that allow the most effective antimicrobial effect on the viable population of Salmonella spp. Thus, Salmonella Enteritidis ATCC 13076 and Salmonella Schwarzengrund were exposed to different time frames, ranging from 5 min to 38.5 min, temperatures between 5 and 38.5 °C, and NaClO concentrations ranging from 0.36 to 6.36 ppm, through a central composite rotational design experiment (CCRD). The results demonstrated that the ATCC strain exhibited a quadratic response to sodium hypochlorite when combined with exposure time, indicating that initial contact would already be sufficient for the compound's action to inhibit the growth of the mentioned bacteria. However, for S. Schwarzengrund (isolated directly from fish cultivated in aquaculture), both NaClO concentration and exposure time significantly influenced inactivation, following a linear pattern. This suggests that increasing the exposure time of NaClO could be an alternative to enhance Salmonella elimination rates in fish slaughterhouses. Thus, the analysis indicates that the Salmonella spp. strains used in in vitro experiments were sensitive to concentrations equal to or greater than the recommended ones, requiring a longer exposure time combined with the recommended NaClO concentration in the case of isolates from aquaculture.

Decolorisation of textile wastewater using biosynthesised iron oxide nanomaterials and Optimisation by Response Surface Methodology

AbstractIn this study, the bacteria (Pseudomonas sp.) was isolated and cultured for biogenic fabrication of Fe3O4 (synthesised using bacterial cell mass) and Fe3O4@ME (synthesised using bacterial extracts) nanoparticles. The biomolecules of the bacterial extract function as a reducing and capping agent, giving the nanoparticle surface negative charges, according to the FTIR and Z potential analysis. The parameters were optimised and screened for indigo blue (IB) dye adsorption onto Fe3O4 and Fe3O4@ME nanoparticles. This work used the Design of the Experimental (DoE) method rather than the conventional one‐variable‐at‐a‐time method. The central composite design (CCD) experiment consisted of 13 experimental runs, and an analysis of variance (ANOVA) was performed to analyse the results. The models for IB dye removal using Fe3O4 and Fe3O4@ME nanomaterials showed adjusted R2 values of 0.99 and 0.99 and predicted R2 values of 0.97 and 0.99, respectively, indicating good model fit. The optimum conditions required for 70 and 64 % colour removal for Fe3O4 and Fe3O4@ME nanomaterials, respectively, are observed at 0.050 gm sorbent doses at the constant room temperature and contact time of 100 min.

Process monitoring by deep neural networks in directed energy deposition: CNN-based detection, segmentation, and statistical analysis of melt pools

The complex interaction between laser and material in Laser Wire Direct Energy Deposition (LW-DED) Additive Manufacturing (AM) benefits from process monitoring methods to ensure process stability and final part quality. Understanding the relationship between process parameters and melt pool geometrical characteristics can be used to effectively monitor and in-process control the process, as the melt pool geometrical characteristics serve as crucial indicators of process stability and quality.This study presents a novel in-situ monitoring approach for LW-DED, utilizing process images for melt pool segmentation, melt pool geometrical characteristics estimation, process stability assessment, and bead geometry prediction. The segmentation of melt pool objects was successfully accomplished using Convolutional Neural Networks (CNN)-based models, enabling the prediction of essential parameters such as melt pool area, height, width, center of area, and the center point of the bounding box enclosing the melt pool. Multiple models were compared regarding the accuracy and processing speed using a controlled central composite design and random experiments. We used an Inconel alloy 625 wire and two distinct substrate materials for deposition, a coaxial laser welding head with a 3 kW fiber laser, and an off-axis welding camera for monitoring.Among the CNN architectures evaluated, YOLOv8l demonstrated superior accuracy with mean Average Precision (mAP) values of 0.925 and 0.853 for Stainless Steel (SS) and low carbon steel (S355) substrates, respectively. Additionally, YOLOv8s exhibited a notable processing speed of over 114 frames per second, which indicates its suitability for real-time process control. Furthermore, the results indicate a significant correlation between process parameters and melt pool geometry variables. Notably, a clear correlation was established between melt pool characteristics and bead geometries obtained through microscopic examinations, including penetration depth and heat-affected zone. The analysis revealed a significant correlation for the bead area and width parameters. In relation to the bead height, while the correlation exhibited a lower magnitude compared to bead area and width, it remained responsive. In addition, the tensor masks derived from the developed models have proven to be highly effective in accurately predicting bead geometries.The results demonstrate the effectiveness of YOLO-based algorithms for detecting and segmenting the melt pool. Statistical analysis confirms the significance of stabilized process data and the accuracy of melt pool geometric models. We demonstrate that integrating advanced monitoring and control techniques using artificial intelligence methods like CNN can facilitate process stability and quality control.

Enhancement of dissolution and oral bioavailability by adjusting microenvironment pH in crocetin ternary solid dispersions: Optimization, characterization, in vitro evaluation, and pharmacokinetics.

The most promising active ingredient of Crocus sativus L., crocetin (CCT), has been demonstrated to possess many biological activities. However, only a few studies have been conducted on CCT formulation, especially in oral formulation, mainly due to its insolubility in water, which limits its application for oral administration. This article reports an equilibrium saturation solubility and single-pass intestinal perfusion studies conducted to classify the biopharmaceutics classification system (BCS) of CCT. To enhance in vitro dissolution and in vivo oral bioavailability, ternary solid dispersions of CCT (CCT-SDs) with soluplus (SOL) as hydrophilic carrier and meglumine (MEG) as alkalizer were optimized using response surface methodology (RSM) with central composite design (CCD) experiments. Four different preparation methods were evaluated using the optimal formulation, including solvent evaporation, ball milling, spray drying, and freeze-drying. Prepared formulations were characterized by TG-DSC, FTIR, X-RPD, and SEM; the pharmacokinetic studies were performed in rats after oral administration. The cumulative dissolution rate of CCT-SDs containing SOL and MEG prepared by the ball milling method was 97.1% at 15min and remained at 95.6% at 480min, which was significantly higher than that of untreated CCT. The lower crystallinity, smaller particle size, and higher microenvironment pH (pHM) were observed in CCT-SDs prepared by the ball milling method. In vivo absorption of CCT-SDs (Cmax = 52.789 ± 12.441μg/mL and AUC0-12 = 191.748 ± 35.043μg/mL·h) was greater than untreated CCT (Cmax = 5.918 ± 1.388μg/mL and AUC0-12 = 44.309 ± 7.264μg/mL·h). In conclusion, the current study provides ternary solid dispersion formulation of CCT to increase the in vitro dissolution and in vivo bioavailability, which will benefit the commercial production and future clinical applications of CCT.

Enhancing the formation of eco-friendly CO2 adsorbent through utilizing the RSM technique and implementation of PAN/PU electrospinning and radiation-grafted approaches

In this research, the original, efficient, novel NF-PAN/PU-GMA-EA nanocomposite was fabricated and used as an adsorbent to remove carbon dioxide from methane. For this purpose, two cheap polymers, including industrial polyacrylonitrile (PAN) and industrial polyurethane (PU) were used to prepare NF-PAN nanofibers under the electrospinning method. Then, the synthesis procedure was performed by grafting glycidyl methacrylate (GMA) onto NF-PAN nanofibers and ethanolamine (EA), diethylamine (DEA), and triethylamine (TEA) as the modified agents. In addition, the response surface methodology based on the central composite design experiments was developed to predict adsorption capacity. The aforementioned approach determined the impacts of GMA monomer (10–30%); gamma radiation at doses (10–50 kGy); and amine concentrations (40–100%). The results showed that ethanolamine was the best amine to modify the surface of NF-PAN/PU nanofibers. The highest adsorption was obtained equal to 2.95 mmol CO2/g adsorbents at a radiation dose of 28.03 kGy, 25.77% GMA and 66.45% EA. The results described that the variation from micro to nanoscale increases the adsorption capacity. Also, a significant increase in the adsorption capacity in the radiation-grafted adsorbent was observed equally to be 73.15% higher than the non-irradiated adsorbent. The adsorption capacity was decreased by about 9% after four adsorption and desorption cycles (regeneration at 80 °C and 15 min), indicating the proper performance of the novel eco-friendly synthesized adsorbents.

Calibration of Small-Grain Seed Parameters Based on a BP Neural Network: A Case Study with Red Clover Seeds

In order to enhance the accuracy of discrete element numerical simulations in the processing of small-seed particles, it is essential to calibrate the parameters of seeds within the discrete element software. This study employs a series of physical tests to obtain the physical and contact parameters of red clover seeds. A discrete element model of red clover seeds is established. Plackett–Burman Design, steepest ascent, and Central Composite Design experiments are sequentially conducted. The simulation deviation of the resting angle of red clover seeds is employed as the evaluation criterion for parameter optimization. The results indicate that the coefficients of static friction between red clover seeds, the coefficients of rolling friction between red clover seeds, and the coefficients of static friction between red clover seeds and the steel plates significantly influence the resting angle. Modeling was performed using a backpropagation neural network, a genetic algorithm–optimized BP network, particle swarm optimization, and simulated annealing. It was found that GA-BP ensured both accuracy and stability. Compared to the traditional response surface methodology, GA-BP showed better fitting performance. For the optimized red clover seed simulation, the error between the angle of repose and the physical experiment was 0.98%. This research provides new insights into the calibration of small-grain seed parameters, demonstrating the value of GA-BP for precision modeling.

Response surface methodology-based characterization and optimization of fibre reinforced cemented tailings backfill with Slag

ABSTRACT With the increasing depths of underground mines due to the scarcity of near-surface ores, the introduction of fibre-reinforced cemented paste backfill (F-CPB) has emerged as a novel solution to address the demanding geomechanical conditions in deep mining operations. However, the widespread adoption of F-CPB in mining and industrial backfill operations necessitates a comprehensive understanding of its key engineering properties, including strength, yield stress, modulus of elasticity, and cost. Moreover, it is crucial to investigate the influence of the constituent materials (water, fibres, binders, tailings) and their interactions on these properties. This research paper presents the application of response surface methodology (RSM) to model the effects of binder content (Portland cement/Slag), water content, fibre content, tailings and their interactions on the mechanical and rheological properties, as well as the cost of F-CPB. Central Composite Design (CCD) experiments were conducted, and a high degree of agreement was observed between the experimental and predicted responses. The RSM approach proves suitable for accurately estimating the responses and assessing the interactions between the model parameters and the properties of F-CPB. Furthermore, a combination of RSM and the desirability approach enables the development of an optimisation tool for F-CPB, facilitating the formulation of optimal backfill mixtures. The results obtained from this study highlight the effectiveness of the combined RSM and desirability approach in F-CPB mix proportioning, offering an advanced engineering approach to F-CPB mix design. The proposed design method has the potential to reduce the laboratory testing protocol required for determining the optimal mix composition.

Optimization pilot scale study on ammonia nitrogen removal by bio filter

In order to obtain the optimal conditions for ammonia nitrogen (AN) wastewater treatment by bio filter (BF), the effects of ratio of carbon to nitrogen (C/N), pH, and hydraulic load (HL) on the AN degradation were studied by Response Surface Methodology (RSM). Central Composite Design (CCD) experiments were conducted, and the response of the AN removal rates were fitted to a second-order polynomial model. The analysis of variance showed that the model was accurate and reliable. Through model fitting, the optimal condition for AN removal was: C/N of 18.95, pH of 7.78, and HL of 1.04 d−1. The maximum AN removal rate predicted by the model was 91.90%, accorded with the experimental verification value of 91.37% under the optimal condition. The research provided valuable demonstration for optimizing process parameters on AN removal in BF.