Main Operating Conditions Research Articles

Valorization of agricultural olive waste as an activated carbon adsorbent for the remediation of water sources contaminated with pharmaceuticals

The present study investigates the performance of activated carbon from olive pomace (ACOP) in the removal of hydrophilic organic pharmaceutical micropollutants such as the antibiotic sulfamethoxazole (SMX) from water. The adsorption behavior of two chemically modified ACOP was investigated considering their interesting textural properties, relevant surface functions and charges. The performances in terms of adsorption capacity were investigated and optimized with respect to the main operating conditions. Comparison of SMX adsorption capacities on ACOP with commercial powdered activated carbon and nanoporous carbonaceous materials prepared from argan shells revealed that ACOP enabled the highest adsorption capacities (39.68 mg g−1). The adsorption behavior was attributed not only to the textural properties, such as the large surface area (1857 m2 g−1) and porosity, but also to the charge and functional groups of the surface.

Influence of main operating conditions on contact wire wear of rigid catenary lines

A validated overhead conductor rail and a well-known wear model have been programmed to perform closer-to-reality simulations. Reliable wear rate estimates for two configurations of overhead conductor rails and three models of pantographs at different speeds and supply currents have been obtained. Results show that wear decreases with increasing speed at high currents and when the distances between supports are uniform. In addition, the use of different types of pantographs in the same facility has a positive effect in terms of wear reduction. Consequently, an adequate selection of the operating conditions contributes to reducing the wear rate.

Presence of hazardous chemical elements in low-cost children's toys: A risk to their development in early childhood

ObjectivesThe objectives of the current study was to study the presence of hazardous chemical elements (Ba138, Cd111, Cr52, Pb208, As75, Co59, Cu63, Mn55, Ni60, Se82, Sr88, Zn66 and Hg202) in low-cost children's toys, and the effect of color types on chemical element concentrations. MethodsChildren's toy samples were analyzed using microwave digestion and inductively coupled plasma/mass spectrometry (ICP/MS) method. Samples were prepared into small pieces, and 500 mg of homogenized sample was used for digestion by means of digesting regents HNO3 (65 %, 5 mL) and H2O2 (35 %, 1 mL). During the digestion process, the pressure was held constant at 90 bar and the temperature, hold time, and power were varied 150–170-40° C, 10–30-5 min, 70–90-0 %, respectively. The main operating conditions of ICP/MS were: spray chamber temperature (−20 °C), RF Power (1450 W), nebulizer gas flow (0.9 L/min), auxiliary gas flow (0.8 L/min) and plasma gas flow (14.85 L/min). Samples and blanks were analyzed for 30 s and system was operated in standard mode. ResultsThe excellent method performance was achieved in terms of limit of detection (LOD, 0.001–14.89 µg/L); limit of quantification (LOQ, 0.003–45.12 µg/L); correlation coefficient (R2, 0.975–0.999) with relative standard deviation values (RSD, 0.70–4.98 %). Chemical elements were found in all the toys (0.01–742.72 ng/g) except sample S2 where only Hg202 was found (0.01 ng/g). Outcomes revealed that the Hg202 was present at a very low level (0.01 ng/g) while Zn66 was present at very high level (742.72 ng/g). Furthermore, the toys contamination was also found to be color-specific, with significant amount of chemical elements was found in black type car sample (S5, 946.98 ng/g) whereas other color type samples constitute lower amounts (0.001–210.53 ng/g). Low-cost toys designed for children's use are found to contain chemical elements that should be addressed in the course of action. As a result of exposure to high amounts of chemical elements in toys, children have a high chance of developing cancer.

Treatment of Coking Wastewater Using Hydrodynamic Cavitation Coupled with Fenton Oxidation Process.

Effective and economical processes for the advanced treatment of coking wastewater were urgently needed to reduce the persistent organic pollutants of external drainage. In the present work, we investigated the degradation of organic pollutants in coking wastewater through IHC/FO (imping stream hydrodynamic cavitation (IHC) coupled with the Fenton oxidation (FO) process) and IHC alone for their feasibility in the advanced treatment of coking wastewater. To select the optimum parameters, attention was paid to the effects of main operation conditions including inlet fluid pressure, medium temperature, initial pH, reaction time, and initial Fe(II) and initial H2O2 concentrations. The results showed that the effects of conditions that need energy to be maintained (such as initial pH and inlet pressure) on the organic pollutant removal efficiency through IHC/FO were less pronounced than those through IHC alone. Moreover, the application of IHC/FO could remove more organic pollutants from coking wastewater than IHC even at an energy-efficient condition. For example, the highest COD removal efficiency of 12.5% was achieved in the IHC treatment at 0.4 MPa, pH 3, and 60 min for the reaction time. In the case of IHC/FO, the maximum COD removal of 33.2% was obtained at pH 7, 0.1 MPa, 12 mmol/L H2O2, and 3 mmol/L Fe2+ after reacting for 15 min. The ultraviolet and visible spectrophotometry (UV-Vis) absorption spectra and gas chromatography and mass spectrometry (GC-MS) analysis further revealed that the kinds and amounts of pollutants (especially those that had benzenes) remaining in water treated through IHC/FO were much fewer and smaller than in water treated through IHC alone. The better performances of IHC/FO than IHC alone were likely related to the more hydroxyl radicals produced through IHC/FO. Taken together, our findings indicate that IHC/FO has great application potential in the advanced treatment of coking wastewater.

Numerical simulation of droplet dispersion within meso-porous membranes

Analysis of membrane processes in fluid processing, and their main influencing operating conditions are relevant in a variety of industrial applications. Increasing regulatory scrutiny and environmental considerations are forcing industries across all sectors, from food and pharma to oil and gas, to further understand and optimise the handling and formulation of liquid systems for efficient process design. In a generic setup for emulsification and liquid formulation the flow and dispersion behaviour of a liquid oil droplet on its way through a porous water filled membrane is analysed. A set of high-resolution numerical simulations of a single oil droplet dispersed in water through a porous membrane structure with varying contact angles is performed. In this work cluster analysis of volume-of-fluid simulation results to obtain statistical droplet size distributions is conducted and further analysed to highlight the effect of the contact angle as well as pressure drop on the dynamics of the system. It is observed that based on the membrane surface activity the droplet behaviour changes from filtration with coalescence when the membrane is lipophilic to emulsification with droplet break-up when the membrane is lipophobic. Furthermore, the pressure drop is identified as a key factor for the dynamics of the droplet process and the frame in which it occurs. These results highlight that the membrane wettability is a determining factor for the emulsification or filtration effectiveness of a membrane for various applications.

Analysis of the Debt-paying Ability of Listed Companies: A Case Study Using BYD Company as a Sample

This paper gives a complete knowledge of BYD’s financial performance through a thorough examination of its financial statements and related indicators. First, the history and development of BYD company are reviewed, and its main business scope and operating conditions are summarized to provide comprehensive background information for the subsequent solvency analysis. Second, this study uses the theoretical framework of solvency to define the important elements that influence solvency, as well as to introduce the generally used solvency evaluation indicators. Finally, in light of the research findings, a number of improvement solutions are offered, including asset structure adjustments and capital structure optimization, to improve BYD’s solvency. The study’s findings seek to provide investors, management, and researchers with a thorough grasp of BYD’s financial status, as well as practical ideas for future development.

Influence of Cold Plasma Processing on the Stability of Phenolic Compounds of Araça-Boi (Eugenia stipitata) Juice

Knowledge of the chemical changes caused during plasma treatment is essential to enhance food quality. In this work, the influence of two cold plasma technologies, dielectric barrier discharge plasma and glow discharge plasma, on the phenolic profile of araça-boi (Eugenia stipitata) juice was investigated and assessed by gas chromatography coupled to mass spectrometry. Eight phenolic compounds were identified in araça-boi, with cinnamic acid being the major phenolic compound of the fruit juice, followed by protocatechuic acid. The effects of excitation frequency and plasma flow rate were evaluated because these are the main operating conditions that can be set for plasma treatments. The phenolic profile slightly changed due to the reaction of the phenolics with the reactive plasma species produced during the treatment, with the highest increase in phenolic content observed in the dielectric barrier discharge plasma operating at 1000 Hz. Both plasma systems increased the bioavailability of phenolic compounds in the juice, which could be increased by up to 201% using the dielectric barrier discharge plasma. Plasma application increased the concentration of cinnamic, hydrocinnamic, benzoic, and p-coumaric acids. Overall, plasma treatment improved the bioavailability of the phenolic compounds and resulted in slight changes to the phenolic profile of araça-boi juice. Thus, the technology showed a positive effect on araça-boi juice. This work advanced our further understanding of the changes induced by cold plasma treatment on phenolic compounds and characterization of araça-boi (Eugenia stipatata).

Technical structure and influencing factors of nitrogen and phosphorus removal in constructed wetlands.

Constructed wetlands purify water quality by synergistically removing nitrogen and phosphorus pollutants from water, among other pollutants such as organic matter through a physical, chemical, and biological composite remediation mechanism formed between plants, fillers, and microorganisms. Compared with large-scale centralized wastewater treatment systems with high cost and energy consumption, the construction and operation costs of artificial wetlands are relatively low, do not require large-scale equipment and high energy consumption treatment processes, and have the characteristics of green, environmental protection, and sustainability. Gradually, constructed wetlands are widely used to treat nitrogen and phosphorus substances in wastewater. Therefore, this article discusses in detail the role and interaction of the main technical structures (plants, microorganisms, and fillers) involved in nitrogen and phosphorus removal in constructed wetlands. At the same time, it analyses the impact of main environmental parameters (such as pH and temperature) and operating conditions (such as hydraulic load and hydraulic retention time, forced ventilation, influent carbon/nitrogen ratio, and feeding patterns) on nitrogen and phosphorus removal in wetland systems, and addresses the problems currently existing in relevant research, the future research directions are prospected in order to provide theoretical references for scholars' research.

Membrane crystallization for recovery of lithium carbonate crystals: Study on process parameters and salts effect for Li2CO3-NaCl-KCl-LiCl solutions

In this work, membrane crystallization (MCr) process was employed for recovery of lithium carbonate (Li2CO3) crystals from synthetic brine solutions. First, the effect of the main operating conditions in MCr, including feed temperature (40, 50, and 60 °C) and flowrate (0.81, 1, and 1.3 L/min) was investigated on the crystallization of Li2CO3 in a binary solution. Next, the effect of main inorganic salts in the brine solutions (i.e., NaCl, KCl, and LiCl) and the mixture of them on the MCr performance and crystallization of Li2CO3 were investigated. In-line microscope, light microscope, scanning electron microscope, and X-ray diffraction test were used to observe the crystallization and characterize the obtained crystals. The obtained results revealed that feed temperature is the main parameter to dominate the nucleation and crystal formation and growth. Thus, the higher the feed temperature, the faster the crystal formation and the larger the crystals. The average crystal size increased from 9.59 to 30.51 μm, when the feed temperature increased from 40 to 60 °C, respectively. However, smaller crystals were observed with adding NaCl and KCl to the solution. Moreover, none of the operating parameters nor the salts additives did affect the crystals shape and the obtained Li2CO3 crystals possess needle-like shape.

Application of Machine Learning to Characterize the Permeate Quality in Pilot-Scale Vacuum-Assisted Air Gap Membrane Distillation Operation.

Membrane distillation (MD) is a thermal desalination technique proposed for the valorization of residual brines that other operations such as reverse osmosis cannot treat. Previous studies have shown that vacuum-assisted air gap (V-AGMD) operation in commercial multi-envelope modules improves the performance of MD noticeably. However, the permeate quality at pilot scale has not been thoroughly characterized so far. The aim of this study is, therefore, to assess and model the effect of the main operating conditions (feed flow rate, inlet temperatures, and feed salinity) on the permeate quality. Results from different steady-state experiments allowed to estimate descriptive metrics such as the salt rejection factor (SRF) and the membrane leak ratio (MLR). Given their non-linear behavior, these metrics were subsequently modeled using artificial neural networks (ANN) to estimate the permeate quality in the whole scope of operating conditions. Acceptable SRF results with MLR values lower than 0.2% confirmed the validity of MD as an operation for the treatment of concentrated brines, although the salinity of the resulting permeate does not comply in all cases with that permitted for human consumption.

Steps to understand the role played by the main operating conditions in the oxidative steam reforming of biomass fast pyrolysis volatiles

Biomass pyrolysis and in-line catalytic oxidative steam reforming of the volatiles (P-OSR) has been analyzed in a two-step reaction system made up of a conical spouted bed reactor (CSBR) and a fluidized bed reactor (FBR). A novel O2 multi-point injection system has been designed in order to ensure suitable O2 distribution in the FBR, and hence avoid the formation of hot spots that may lead to irreversible catalyst deactivation by metal sintering. Optimization of the main process parameters has been approached in order to maximize H2 production and overcome the high energy requirements of the endothermic reforming reaction. The study has been conducted in the following ranges of the operating conditions: Reforming temperature, 550–700 °C; space time, 5–20 gcat min gvolatiles−1; steam/biomass (S/B) ratio, 2.5–5; and equivalence ratio (ER) from 0 to 0.19. Moderate reforming temperatures (600–650 °C), a S/B value of 3 and a space time of 15 gcat min gvolatiles−1 are the optimum conditions for the process. Furthermore, when low space time values are used, O2 feeding rates into the reforming step of up to an ER value of 0.12 (corresponding to autothermal operation (ATR)) revealed a synergistic effect promoting reforming reactions. Thus, an improvement in H2 production from 6.81 wt% to 8.26 wt% was observed by changing ER from 0 to 0.12, which means H2 production increases by 21.4% compared to the conventional pyrolysis-reforming (P-SR) process. Therefore, the promising results obtained in this study prove the suitability of the continuous P-OSR strategy for H2 production from biomass and involve a step forward towards the scaling up of the process.

Development of a spray-ejector condenser for the use in a negative CO2 emission gas power plant

One promising solution for developing low-emission power technologies is using gaseous fuel combustion in pure oxygen when the exhaust gas mixture is composed of H2O and CO2, and where CO2 is separated after steam condensation. The paper presents the results of computational analyses providing to the Spray-Ejector Condenser (SEC) development, which is one of the crucial components of the negative CO2 gas power plant (nCO2PP) cycle development. The proposed design of the ejector-condenser to ensure the high effectivity of vapor condensation and CO2 compression with preparation to separation, ready for application in gas power cycle, is a novelty of this research. Different computational techniques leading to the development and better understating of ejector operation were applied. The main operating conditions in the characteristic connected with the developed nCO2pp cycle points were investigated to evaluate the impact of the operating conditions on SEC performances. The amount of motive water needed for the cooling purpose is susceptible to the inlet water pressure and temperature and strongly affects the generated pressure of the suction stream. The preliminary results confirm that the SEC's basic design and geometrical dimensions can be applied in the negative CO2 power plant cycle. Results from CFD modeling give the possibility to investigate the turbulent flow of water/steam/CO2 mixture together with the condensation process occurring at this same time. It is found that the average droplet diameter and motive water supplying method significantly effects the condensation intensity. The further direction of the presented computational research activities and results is to test various designs of Spray-Ejector Condensers that will enable the evaluation of the direct contact condensation process and develop the final geometrical design.

Experiments and machine learning-based modeling for haloacetic acids rejection by nanofiltration: Influence of solute properties and operating conditions

Because of potential risks to public health, the presence of haloacetic acids (HAAs) in drinking water is a major concern. Nanofiltration (NF) has shown potential for HAAs rejection, and several factors, namely, membrane properties, solute properties, and operating conditions, have been revealed key roles. However, knowledge of NF separation mechanism by quantifying these factors is limited. This study investigated and modeled NF performance on HAAs rejection. NF performance was experimentally investigated under various transmembrane pressure (TMP), cross-flow velocity (CV), temperature, pH, ionic strength (IS), and HAAs initial feed concentration (Cin). We used machine learning (ML) to understand the mechanism from the perspective of HAAs properties and operating conditions. Multiple linear regression (MLR), support vector machine (SVM), multsilayer perceptron (MLP), extreme gradient boosting (XGBoost), and random forest (RF) models were used. The MLP, XGBoost and RF models achieved significant performance with high R2 (0.970, 0.973, and 0.980) and low RMSE (4.71, 4.41, and 3.84). These three models were analyzed using the Shapley Additive explanation (SHAP) to quantify relative contributions of HAAs properties and operating conditions. XGBoost-SHAP produced the most logical results and was the best-performing model for selecting optimal input variables combinations. The results showed that Stokes radius (rs), logarithmic octanol-water partitioning coefficient (logKow), molecular weight (MW), pH, TMP, and temperature are key variables for interpreting NF process. The effects of HAAs properties were ranked as rs > logKow > MW, suggesting significance of size exclusion and hydrophobic interaction. The impact of the operational conditions followed the order pH > TMP > temperature, illustrating that pH was the major influencing operating condition. This study demonstrated significant capacity of ML, which reduced amount of experimental work. In addition, the main operating conditions can be evaluated in terms of their contributions, making ML an efficient tool for risk management and process optimization.

CATALYTIC HYDROTHERMAL CONVERSION OF BIO-DERIVED SUGARS FOR LACTIC ACID PRODUCTION USING SOL-GEL SYNTHESIZED ZIRCONIA

The hydrothermal conversion of a multiple sugars solution (xylose, arabinose and glucose) was studied using high surface ZrO2-based catalysts to produce lactic acid. The catalysts were synthesized by template-assisted sol-gel method and alternative template removal procedures. Samples obtained by template extraction with solvent reported a specific surface area of 323 m2/g, a pore volume of 0.21 cm3/g and a total amount of acid sites of 359 µmol/g. An experimental design was performed to model lactic acid and by-products obtaining around the selected catalyst. The response surface methodology (RSM) was used to optimize the main operating conditions. A mass selectivity of 35.1 % towards lactic acid was found at 183 °C and 212 min. In addition, the reaction mechanisms involved were proposed based on intermediates and degradation compounds detected by HPLC analysis.

Sorption enhanced steam methane reforming in a bubbling fluidized bed reactor: Simulation and analysis by the CPFD method

This work reports the modelling and simulation results of a bubbling fluidized bed reactor using the Computational Particle Fluid Dynamics (CPFD) method of the Barracuda® software. The reactor under investigation is the carbonator installed in the ENEA ZECOMIX research infrastructure, where Steam Methane Reforming (SMR) happens simultaneous with CO2 capture via solid sorbents. In this intensified process, namely Sorption Enhanced Steam Methane Reforming (SE-SMR), steam methane reforming is coupled with high temperature CO2 sorption and calcium looping (CaL) process, in order to increase the H2 yield, beyond thermodynamic limits. Currently, the reactor is operated in batch mode and is used also for sorbent regeneration, by switching the fluidizing gas flow from steam/methane to oxy-burner combustion products. With the aim of studying the process when it is operated as a closed loop, in this paper the reactor is continuously fed by a fresh sorbent flow and a riser/calciner reactor for sorbent regeneration, to be connected with the carbonator, has been sized. The continuous circulation of solid material between the two reactors ensures the maintenance of different operating temperatures and therefore greater operational optimization.The numerical analysis presented in this paper will serve as a valid support for the experimental activities. For this purpose, a sensitivity study on the SE-SMR process has been conducted, by varying the main operating conditions (e.g. sorbent conversion, sorbent/catalyst ratio, fluidizing gas flow), to evaluate the hydrogen purity yield. Two different kinetic mechanisms have been compared for the gas phase reactions. A post-processing routine has been written, in order to analyze bubbles sizes and velocities inside the fluidized environment. The effect of sorbent and catalyst particles segregation has been also investigated. The same modelling approach has been used for the sizing of the fast riser calciner reactor.

Experimental investigation of sulfur distribution and yields of liquid fuel and petroleum coke produced by thermal cracking of vacuum residues

In the present work, an experimental study was conducted to investigate the sulfur distribution in the products during thermal degradation of vacuum residues at different operating conditions. In this regard, three vacuum residues with different sulfur contents were selected. The effects of main operating conditions such as pressure and temperature on products yields and properties were studied. The results show that for sulfur distribution, which is indicated as the ratio of the amount of sulfur in each product to the initial mass of sulfur in the feed, increasing temperature will be followed by increased sulfur distribution in liquid fuel and reduced sulfur distribution in petroleum coke. Furthermore, effects of reaction temperature on yields of light coker gasoil (150–350 °C) as well as heavy coker gasoil (350–500 °C), as the dominant fractions of thermal cracking products, were evaluated using simulated distillation method.

Photo-Fenton oxidation of cylindrospermopsin at neutral pH with LEDs

Cylindrospermopsin (CYN) is a potent cyanobacterial toxin found in freshwaters worldwide. In this work, the feasibility of the photo-Fenton process under neutral pH using light emitting diodes as irradiation source for the removal of this hazardous cyanotoxin from freshwater was investigated. The impact of the kind of iron chelating agent (ethylenediamine-N, N′-disuccinic acid vs. ethylenedinitrilotetraacetic acid) as well as the effect of the main operating conditions viz. H2O2 dose, Fe(III) load, initial CYN concentration, and Fe(III):EDDS molar ratio on the performance of the process was systematically evaluated. EDDS was selected as the most appropriate iron chelating agent considering the kinetics of the process and the environmental impact (Vibrio fischeri and Artemia salina). Under optimized conditions ([H2O2] = 30 mg L−1; [Fe(III)] = 5 mg L−1; Fe(III):ligand = 1:0.5 (molar ratio)), complete removal of CYN was achieved in 15-min reaction time. Furthermore, the catalytic system showed to be effective in real water matrices (river and reservoir waters) spiked with CYN. Although the presence of inorganic ions (mainly HCO3−/CO32−) and dissolved organic carbon decreased the oxidation rate of CYN due to scavenging reactions and iron coordination, respectively, complete elimination of the cyanotoxin was achieved in all cases. The fate of EDDS along the process was also evaluated to demonstrate that the catalytic system investigated, apart from its effectiveness, warrants the complete absence of residues after reaction. Therefore, the proposed system constitutes a promising method for cyanotoxin treatment either as a drinking water treatment step in conventional plants or as a potential remediation strategy in the natural environment.

Glucose and Ethanol Checked by Flow Direct Catalytic Fuel Cell (DCFC) and Energetic Considerations

Aims: A new basic research was conducted concerning the possibility of using a flow DCFC (Direct Catalytic Fuel Cell) for analytical purposes, checking ethanol and glucose. Also making considerations on the energy conversion aspect of these fuels. Background: There are a large number of studies concerning catalytic or microbial fuel cells, which allow to obtain electricity, both using liquid fuels, such as ethanol and methanol, or solid fuels, such as carbohydrates, biomass and so on. These systems are frequently characterized by high conversion efficiency but also high complexity and considerable costs. Objective: In the present research we investigated the possibility of using a very simple flow system to carry out measurement of ethanol concentration, or glucose analysis, using the same flow system associated with a small reactor containing yeast (Saccharomyces cerevisiae). Methods: The main operating conditions have been optimized and the concentration range where the flow system response shows a linear correlation with the fuel concentration was also identified. Result: The current delivered by the catalytic system operating in flow was determined and the calibration sensitivity values are higher than the sensitivity found in batch mode. It has also been shown that it is possible to realize a very simple system, which can be used to study and evaluate the conversion of chemical energy into electrical energy, using ethanol or glucose as fuel and the theoretical importance and analytical advantages have been emphasized, so that the use of carbohydrates, such as solid fuels, could represent. Conclusion: Present research has shown how, by operating in flow mode, rather than in batch, it is possible to have advantages from an analytical point of view, since a considerable increase in the sensitivity of the method can be obtained, probably attributable to a reduction in the effects of poisoning. Moreover, how it is possible to study and optimize the energy conversion conditions by means of a simple and inexpensive apparatus.

Comprehensive operational parameter analysis of cross-flow hollow fiber membrane humidifier for humidification dehumidification desalination

Experimental results show that the cross-flow hollow fiber membrane contactor is the controlling component of the humidification dehumidification desalination system performance. Three sets of main operating conditions sensitivity analyses are performed numerically, including solution conditions (temperature, salinity, flow rate), air conditions (temperature, relative humidity, flow rate) and dimensionless parameters (number of heat transfer units, flow rate ratio of solution to air). Increasing flow rate ratio can effectively promote freshwater production rate before flow rate ratio reaches a critical value of 6.0. It is useful to improve moisture effectiveness by increasing number of heat transfer units. Solution inlet temperature has an exponential promoting effect on membrane flux, which is consistent with the exponential upward trend of the solution phase equilibrium humidity. Membrane flux increases dramatically at first and then slowly after solution flow rate exceeds 228 kg/h and air flow rate exceeds 57 kg/h. Ambient air with high temperature and relative humidity as well as the high salinity of the solution will slightly degrade the membrane flux.

Prediction of microbial growth via the hyperconic neural network approach

The design and control of biological reactors depends upon the correct calibration and selection of kinetic parameters from the exponential phase in the microbial growth. The kinetic microbial parameters that are reported in the literature of biochemical engineering are obtained based on specific growth conditions, which limits their potential application in a wide variety of dynamic models. In this paper, we propose an adaptive machine-learning approach to predict microbial growth, and provide information on the effect that variations of pH and concentration of the culture media have on the growth rate. We study biological reactions and obtain a set of experimental exploratory data using the Pseudomonas aeruginosa (i.e., P. aeruginosa). The versatile and robust metabolism of P. aeruginosa is responsible for its ability to grow in different environment conditions, even at low nutrient and oxygen levels, in a sample range of temperatures (4∘-42∘C) and polluted sites. Our first contribution is to propose a technique to gather experimental data via measurements of optical density, microbial growth, from the Multiskan™ FC Microplate Photometer, Thermo Scientific. Our second contribution consists of building a surrogate model by successfully adapting the Hyperconic Multilayer Perceptron (HC-MLP), a novel computational and mathematical approach, to predict microbial growth across all the set of conditions of the experimental design. HC-MLP is a state-of-the-art method that is used to define complex non-linear decision boundaries, in the parameters’ space, using a mix of ideas from conformal geometry and neural networks, and focusing on quadratic hyper-surfaces through multiple hidden layers. Consequently, we generate precise surrogates, which can even predict microbial growth in values not evaluated during the experimental stage. Finally, our statistical testing and comparisons validate that the proposed experimental, mathematical and computational framework is robust and capable of predicting the dynamic growth of bacteria P. aeruginosa using two main operation conditions: pH and concentration culture media at pH 7.0. In the future, we plan to apply our proposed methodology to other bacterial strains and advance HC-MLP for forecasting dynamics of other multiple microbial measurements under a wide variety of conditions.