Optimal Parameters Research Articles

Numerical and artificial neural network inspired study on step-like-plenum battery thermal management system

This study leverage numerical simulation (NS) and artificial neural network (ANN) capabilities to carry out additional investigations on step-like plenum battery thermal management system (BTMS). Different cooling strategies have been developed over the years in BTMSs’ design. Yet, air-cooling strategies still remains relevant, especially in battery-powered aircrafts, where light-weight is important and air is the preferred cooling fluid. Hence, additional study become necessary especially on the step-like plenum design to provide more insight on the performance of the design by considering several number of step, varied air inlet temperature and velocity. Computational fluid dynamics (CFD) approach was employed to obtained results for different number of step; Ns = 1, 3, 4, 7, 9, 15 and 19, varied air inlet temperature; Ti = 278, 298 and 318 K, and varied air inlet velocity; Vi = 3, 3.5, 4, 5 and 6 m/s. Artificial Neural Network (ANN) approach was then employed to predict the BTMSs’ performance for additional values of Ti and Vi. Minimum temperature (Tmin), maximum temperature (Tmax), maximum temperature difference (ΔTmax) and pressure drop (ΔP) were computed. By comparing the CFD results with the result predicted by the ANN, the percentage difference, for the entire dataset were 0.01 %, 0.005 %, 1 % and 0.14 % for Tmax, Tmin ΔTmax and ΔP, respectively. Based on the optimum design parameters predicted using ANN, for Tmax = 299.24 comprises Ns = 4, Vi = 6 m/s and Ti = 278 K, while for ΔP, comprises Ns = 1, Vi = 3 m/s and Ti = 318 K.

Beyond viability: Advancing CHO cell culture process strategies to modulate host cell protein levels

Chinese Hamster Ovary (CHO) cells are widely utilized in bioprocessing industry for monoclonal antibody (mAb) production. In many instances, challenges persist in achieving sufficient clearance of Host Cell Proteins (HCPs) in the final drug substance. While purification strategies usually offer substantial HCP clearance, certain "problematic" HCPs, particularly lipases, continue to pose significant challenges. This study investigates the accumulation of various "problematic" HCPs in CHO cell culture using transcriptomics, revealing correations between cell culture parameters and HCP level. Contrary to conventional assumptions, viability alone does not reliably predict HCP levels, with factors such as clone selection, host cell line choice, media and feed compositions significantly influencing HCP accumulation. Leveraging transcriptomics-based approaches, we demonstrate the potential of upstream process control strategies to mitigate HCP presence and improve biologic product quality. Our findings underscore the importance of considering diverse cell culture parameters in bioprocess optimization to ensure product stability and quality. While promising, further research is needed to elucidate the mechanisms underlying HCP release and propagation through downstream processing stages, emphasizing the necessity of a comprehensive integrated approach to HCP control in biologics production.

Hydraulic valve design methodology for hydro turbine control system

The control of the turbine and its equipment in a hydroelectric power plant requires the HPU (hydraulic power unit) to deliver large volumes of working fluid in a short time at specific optimum control parameters. The use of typical proportional flow control valves created by manufacturers of hydraulic components in low-pressure control systems is disadvantageous due to high pressure losses in the control chambers. This paper presents the methodology and test results while designing a hydraulic proportional valve for low pressure and high flow rate operation. CFD (computational fluid dynamics) theory was analyzed and characteristic values were determined. The validation of CFD tests through those on the test bench was carried out, correction factor was determined. A new proprietary solution was developed and a series of simulation studies were carried out to determine the flow characteristics depending on the degree of the opening of the proportional flow control valve.

Instrumentation in Tractor for Evaluating Performance of a Tractor Drawn Rotavator

Performance measurement of agricultural machinery is essential for enhancing their efficiency for which they are operated. The performance related data helps the operator to select optimum operating parameters which reduce fuel consumption and increase field productivity. This study was aimed to develop various sensing units and install them on the tractor for evaluating performance of a tractor drawn rotavator. A microcontroller based embedded system was developed for continuous recording of wheel slip, actual forward speed, throttle opening, engine speed, velocity ratio, draft and power take-off (PTO) torque related data while carrying out tillage operation with rotavator. The wheel slip (from 1.5% to 35%) and actual forward speed of the tractor (up to 6 km h-1) was measured using inductive proximity sensors. For measuring throttle opening (0 to 100%), engine speed (750 to 2500 rpm), draft (65 to 350 kg) and PTO torque (up to 420 N-m) values, a potentiometer, magnetic pickup sensor, S-type loadcell and PTO torque transducer, respectively, were used. For computing velocity ratio, peripheral speed of rotavator was measured using PTO speed data received from PTO torque transducer, and actual forward speed of tractor was measured using inductive proximity sensor. The developed sensing units were calibrated under both dynamic and static conditions, and were also verified in laboratory and field conditions. Results showed that output signals received from the sensing units varied linearly with applied load. The mean absolute percentage error (MAPE) between measured and actual values was found to be below 5%. From the measured parameters, specific energy requirement and total power required for carrying out tillage operation could be computed. The power requirement was found to increase with increase in both gear and throttle settings. The specific energy requirement was minimum when rotavator was operated in L2 gear of the tractor. The minimum specific energy of 21 Wh m-3 was found at L2 gear and 75% throttle opening.

Exponential or Unimodal Relationships Between Nighttime Ecosystem Respiration and Temperature at the Eddy Covariance Flux Tower Sites.

Ecosystem respiration is a key flux in the terrestrial carbon cycle and is affected substantially by temperature. This work analysed the time series data of nighttime net ecosystem exchange of carbon dioxide (NEEnight) from 196 FLUXNET2015 sites to re-evaluate the relationships between NEEnight and temperature. A total of 93 sites (48%) were identified to have a unimodal relationship between NEEnight and temperature. Site-specific apparent optimum temperature parameters were then estimated at these sites. We further assessed the impacts of using exponential or unimodal equations on NEEnight predictions. The predicted NEEnight values at high temperatures were substantially higher from the exponential-type equations (mean: ~200%) than from the unimodal equation (mean: ~30%), compared to the observed NEEnight. This study calls for using a unimodal equation to predict NEEnight (often considered as nighttime ecosystem respiration, ERnight), which could substantially improve the accuracy and reduce uncertainty in ER estimates, in particular under the scenario of global warming.

Characteristics of light emission and wear behaviour of a reinforced composite material made of basalt and jute for optimum parameters

Characteristics of light emission and wear behaviour of a reinforced composite material made of basalt and jute for optimum parameters

Synthesis and characterization of a crosslinked deacetylated chitin modified chicken bone waste-derived hydroxyapatite and TiO2 biocomposite for defluoridation of drinking water

This work represents an innovative approach to the synthesis and characterization of a chitosan-based biocomposite for fluoride adsorption. The work involved the development of a biocomposite based on modified chicken bone waste-derived hydroxyapatite and TiO2. The composite was characterized using scanning electron microscopy with Energy Dispersive X-ray analysis (SEM-EDX), X-ray diffraction (XRD), Fourier-transform infrared analysis (FTIR), thermal-gravimetric analysis (TGA), and X-ray photoelectron spectroscopy (XPS). The optimum parameters for fluoride removal were determined, and the kinetic data was better fitted to the pseudo-first-order model. The Liu equations provided a better description of the experimental adsorption isotherm data. The adsorption mechanism and the interaction of the composite with fluoride were better understood using Density Functional Theory (DFT) calculations and Non-Covalent Interactions (NCI) analyses, paving the way for more effective and efficient defluoridation methods.

Harnessing the Plastic-degrading Potential of Pseudomonas Species for Environmental Sustainability

Abstract The prevalent utilization of synthetic plastics in contemporary society has made them indispensable. Nonetheless, the enduring predicament of plastic waste presents challenges to environmental sustainability and effective waste management. Plastic pollution can disrupt habitats and natural processes, diminishing the ecosystem’s resilience to climate change and directly impacting the livelihoods, food production capabilities, and social well-being of people. Moreover, plastic recycling itself can rise the production of polluting microplastic that find their way into water sources or air. In to address the environmental predicaments associated with plastics, it is imperative to examine the intricate interplay between microbes and polymers. Understanding this dynamic relationship is important as we strive to develop effective solutions and mitigate the adverse effects of plastic on our environment. Bacteria evolved strategies to survive and degrade plastics in contaminated environments. In this study, we focused on the ability of Pseudomonas species to degrade different sets of synthetic plastics including Low-Density polyethylene (LDPE), High-density polyethylene (HDPE), polyvinyl and polystyrene. Then a simulation study using kinetic models was conducted to determine optimum parameters for degradation ability. Our results indicate four different Pseudomonas strains P. aeruginosa strains, P. boreopolis and P. dehiensis two strains of which were able to grow in minimum media containing the different plastics as the only carbon sources reflecting their capacities to degrade these complexes polymers. Kinetic modeling for microbial growth of P. aeruginosa using batch and feed batch demonstrated that the feed batch fermentation procedure has the potential to produce Pseudomonas biomass on a larger scale, with a production of 250.7481 g/l after 72 hours. These results enhance their applicability in industrial settings particularly in bioremediation field. These findings highlight the important uses of bacterial strain of Pseudomonas as a promising strategy to depolymerize complex plastics into monomers for recycling or mineralize them into new biodegradable biomass.

Interpretable Model-Driven Deep Network for Hyperspectral, Multispectral, and Panchromatic Image Fusion.

Simultaneously fusing hyperspectral (HS), multispectral (MS), and panchromatic (PAN) images brings a new paradigm to generate a high-resolution HS (HRHS) image. In this study, we propose an interpretable model-driven deep network for HS, MS, and PAN image fusion, called HMPNet. We first propose a new fusion model that utilizes a deep before describing the complicated relationship between the HRHS and PAN images owing to their large resolution difference. Consequently, the difficulty of traditional model-based approaches in designing suitable hand-crafted priors can be alleviated because this deep prior is learned from data. We further solve the optimization problem of this fusion model based on the proximal gradient descent (PGD) algorithm, achieved by a series of iterative steps. By unrolling these iterative steps into several network modules, we finally obtain the HMPNet. Therefore, all parameters besides the deep prior are learned in the deep network, simplifying the selection of optimal parameters in the fusion and achieving a favorable equilibrium between the spatial and spectral qualities. Meanwhile, all modules contained in the HMPNet have explainable physical meanings, which can improve its generalization capability. In the experiment, we exhibit the advantages of the HMPNet over other state-of-the-art methods from the aspects of visual comparison and quantitative analysis, where a series of simulated as well as real datasets are utilized for validation.

Medical-Knowledge-Based Graph Neural Network for Medication Combination Prediction.

Medication combination prediction (MCP) can provide assistance for experts in the more thorough comprehension of complex mechanisms behind health and disease. Many recent studies focus on the patient representation from the historical medical records, but neglect the value of the medical knowledge, such as the prior knowledge and the medication knowledge. This article develops a medical-knowledge-based graph neural network (MK-GNN) model which incorporates the representation of patients and the medical knowledge into the neural network. More specifically, the features of patients are extracted from their medical records in different feature subspaces. Then these features are concatenated to obtain the feature representation of patients. The prior knowledge, which is calculated according to the mapping relationship between medications and diagnoses, provides heuristic medication features according to the diagnosis results. Such medication features can help the MK-GNN model learn optimal parameters. Moreover, the medication relationship in prescriptions is formulated as a drug network to integrate the medication knowledge into medication representation vectors. The results reveal the superior performance of the MK-GNN model compared with the state-of-the-art baselines on different evaluation metrics. The case study manifests the application potential of the MK-GNN model.

Experimental Design, Statistical Analysis, and Modeling of the Reduction in Methane Emissions from Dam Lake Treatment Using Agro-Industrial Biochar: A New Methane Capture Index

This study aimed to reduce the methane (CH4) emissions originating from dam lake treatment using malt dust-derived biochar, which is an agro-industrial byproduct of the brewery industry. Optimum operating and water quality parameters for CH4 reduction were determined using statistical analyses based on the Box–Behnken design method. Also, a Monte Carlo simulation was performed to determine the correlation between CH4 emissions and operating parameters. According to the simulation, dissolved oxygen (DO) and the oxidation–reduction potential (ORP) had the highest correlation with CH4 emissions, with values of 92.03% and 94.57%, respectively. According to the Box–Behnken design methodology, the optimum operating parameters were 4 mg/L of dissolved oxygen, −359 mV of ORP, and 7.5 pH for the minimum CH4 emissions. There was a reported reduction of up to 19.4% in CH4 emissions for the dam lake treatment using malt dust-derived biochar. Finally, a new methane capture index, based on the biochar application (MCI), was developed and validated. The largest methane capture capacity was related to the malt dust-derived biochar produced at the lowest temperature (M1).

Parameter Calibration of Chaboche Kinematic Hardening Model by Inverse Analysis Using Different Optimization Methods in the Case of Pipe Bending

Drag link is one of the important parts in steering system used in automotive. The ball joint, ball joint housing, and pipe compose the drag link. In this study, finite element analysis is used to simulate the deformation process. St 52 steel material is used. A yield criterion, an associated flow rule, and Chaboche’s kinematic hardening rule were used in the finite ele-ment simulations of processes involving high plastic deformation. A series of low-cycle ten-sile/compression tests is performed to determine the parameters of Chaboche’s kinematic hardening rule. The success of the simulation results depends on the more accuracy of the finding parameters. Some optimization methods are used in the calibration progression of these parameters and the results are compared. For the purpose of optimization, the angle of the pipe after bending is set as 16.6 as soon as possible. As design variables, the Chaboche kinematic hardening rule parameters were adjusted. Consequently, calibrated parameters were obtained for St52 pipe bending. By analysing and verifying the candidate points, opti-mization methods are compared. The optimum parameters are determined as YS=350 MPa, C=2984.3 MPa, and =100 while their initial values are YS=373.806 MPa, C=4016 MPa, and =94. It is concluded that the optimization process gives more consistency in the bending process.

Features of MHD on Secant Curved Annular Circular Plate Lubricant as a Couple-Stress Fluid with Slip Velocity

The purpose of this study is to examine the magneto-hydrodynamic (MHD) and slip velocity effect on secant curved annular circular plates lubricated with couple stress fluid and to derive the modified Reynolds’s equation for non-Newtonian fluid under various operating conditions to obtain the optimum bearing parameters. Based upon the MHD theory and Stokes theory for couple stress fluid, the governing equations relevant to the problem under consideration are derived. This paper analyses the effect of slip velocity on secant curved annular circular plates with an electrically conducting fluid in the presence of a transverse magnetic field. It is found that there is an increase in squeeze film pressure, load carrying capacity and squeeze film time in secant curved annular circular plates due to the presence of magnetic effects with couple stress fluid and slip velocity.

Effect of Winter Sowing and Different Fertilizer Sources on Physiological Parameters and Yield Components of Dragon’s Head (Lallemantia iberica Fisch. & C.A.Mey.)

The effects of autumn sowing and chemical, organic, and biological fertilizer sources were explored on yield components and physiological traits of dragon’s head (Lallemantia iberica Fisch. & C.A.Mey). The study was conducted as a factorial experiment based on a randomized complete block design with three replications in a field experiment in the 2017-2018 crop year. The fertilizer treatments included organic fertilizers (vermicompost, manure, and humic acid), biofertilizer (Thiobacillus mixed with sulfur), chemical fertilizer (macro NPK), and control (no fertilizer). The studied traits included seed yield per ha, harvest index, biological yield per ha, chlorophyll a, chlorophyll b, carotenoid, proline, and dissolved carbohydrate. The results of the comparison of the means revealed that the winter sowing outperformed the spring sowing evidently and increased traits like seed yield per ha, biological yield per ha, and harvest index significantly. The fertilization of the plants in both sowing seasons, especially in the winter sowing, increased seed yield per ha, biological yield per ha, and harvest index so that the vermicompost-fertilized winter-sown plants produced the highest seed yield per ha (0.91 g), whereas the application of manure was related to the highest harvest index in the winter sowing (27.9%). The highest biological yield (8797 kg ha-1) was related to the treatment of Thiobacillus of the winter-sown plants. Proline content was higher in the spring sowing plants, and the control treatment in the spring sowing had the highest proline content (0.120 mg g-1). Concerning dissolved carbohydrates, the spring sowing and the unfertilized plants had the highest content (20.3 mg g-1). On the other hand, chlorophyll a, chlorophyll b, and carotenoid were higher in the treatments of Thiobacillus and vermicompost, which resulted in achieving higher yields due to the increase in photosynthesis rate. According to the results, the winter sowing of the dragon’s head in the Azerbaijan region of Iran and the use of Thiobacillus and vermicompost could be recommended for obtaining plants with optimum quality parameters.

Impacts of Zirconium Carbide Incorporated Magnesium Alloy Nanocomposite on Wear Properties

In the study, zirconium carbide nanoparticle (ZrC-50 nm) incorporated magnesium alloy (AZ61) nanocomposite was prepared by liquid state stir cast process, and its wear properties were evaluated by different load (U), sliding speed (V), and sliding distance (W). The impacts on wear rate (WR) and coefficient of friction (COF) of AZ61 alloy nanocomposite were studied. With the support of a pin-on-disc wear tester, the dry sliding wear characteristics were measured. Moreover, to find the optimum process parameter on minimum WR and better COF characteristics, the L27 orthogonal array utilized U, V, and W as the input factors, and the WR & COF were treated as output responses. Based on the analysis, load was found to be the most dominant input factor that influences the WR and sliding distance was the factor for fixing the COF.

Evaluation of Postharvest Quality of Fresh Kesum Leaves (Persicaria minor) during Storage in Different Temperatures and Packaging

Persicaria minor, locally known as kesum, is an herb synonym in Southeast Asia as a food flavor enhancer and seasoning for Eastern delicacies. Kesum leaves are quickly wilted, shrink, and lose moisture once harvested. This study aimed to determine optimum parameters: storage temperature and suitable packaging to maintain the freshness and quality of kesum and prolong the storage life. This study consisted of two activities: determining the best storage temperature and determining suitable packaging. For the first activity, kesum leaves were harvested manually from matured plants, transported to a packinghouse, sorted, cleaned, packed, and sealed in polyethylene (PE) 0.04mm before being stored at different temperatures, which were 5°C, 8°C, 10°C and 13°C, while for the second activity, kesum leaves were packed and sealed in different packaging: polyethylene (PE) 0.04mm and polypropylene (PP) 0.04mm and stored at 5°C. The postharvest quality of all samples and treatments (weight, moisture content, pH, total titratable acidity, total soluble solids, respiration rate of the leaves, total phenolic content, and leaf color values) was measured and recorded weekly throughout the storage period. The study's results found that storing fresh kesum leaves at 5°C temperature and in PE 0.04mm packaging can delay the senescence and maintain the quality and postharvest attributes for up to 35 days, as shown in lower respiration rate, maintain the pH, total titratable acidity, total soluble solids and color of the leaves, and show higher total phenolic content for up to 35 days of storage compared to storing in temperature of 8°C, 10°C, and 13°C and PP 0.04mm packaging.

Design strategies and systematic analysis of GaN vertical MPS diodes with T-shaped shielding rings

Abstract We report gallium nitride (GaN) vertical merged pn-Schottky (MPS) diodes with T-shaped p-GaN shielding rings (SRs). The embedded T-shaped SR features an overlapped depletion region by the lateral and vertical p n junctions under reverse bias condition, which can effectively enhance the charge coupling effect and homogenize the 2-D electric field distribution. In the meantime, the incorporation of the T-shaped SRs can minimize unnecessary depletion of the vertical conduction channel and guarantee a decent current spreading through the drift region. The impact of the key design parameters on the reverse breakdown and forward conduction performance are investigated systematically. We found that the doping concentration and the geomatical shape of the T-shaped p-GaN SRs are closed related to the electric field distribution and forward current conduction behavior, which determines the reverse breakdown and forward conduction performance. With optimum design parameters of the T-shaped SRs, the breakdown voltage of the MPS diodes features a dramatic improvement to 2749 V from 1123 V in conventional MPS diodes. The results can provide a design strategy for high performance vertical GaN power diodes towards high-power and high-frequency applications.

Activated Carbon derived from Jackfruit Seeds for Oil Adsorption

Activated carbons (AC) are widely used as adsorbents for treating oily wastewater. An effective, cheap and environmental-friendly method for oil adsorption by using AC derived from jackfruit seeds (JS) was developed in this study. The JS were chemically activated with different concentrations (10 wt.% and 15 wt.%) of chemical activating agents (H3PO4 and ZnCl2) to produce activated carbon. The optimum conditions for developing AC from JS with the highest oil adsorption capacity was found using 15 wt.% ZnCl2, and carbonised at 500°C resulting in maximum adsorption capacity of 0.8621 g/g. Raw JS and jackfruit seed-derived activated carbon (JSAC) were characterized by Fourier Transform Infrared Spectroscopy and Scanning Electron Microscopy analysis. The influence of process parameters such as contact times (0 – 240 minutes), adsorbent dosages (0.5 – 2.5 g) and adsorption temperatures (25 – 65 °C) for oil adsorption were investigated. The results showed that the optimum parameters for maximum adsorption capacity were as follows; 120 minutes of contact time, adsorbent dosage of 1.5 g and at 35 °C. At this condition, the highest oil adsorption capacity was achieved at 1.5674 g/g. The adsorption kinetic studies depicted that the oil adsorption mechanism was represented by pseudo-second-order kinetic model which implies that the adsorption is a chemisorption process. Jackfruit seeds had been proven to have the capability as an effective adsorbent for oil adsorption.

Effect of Sodium Cyanide and Jin Chan Chemicals on Gold Gain from Ore

In this article, experiments were carried out on samples taken from two different gold mines located in İzmir Province, Dikili District Çukuralan Locality and Eskişehir Province Sivrihisar District Kaymaz Site. Jin Chan, a new chemical approach with sodium cyanide (NaCN), comparatively evaluated leaching kinetics, gold recovery efficiencies and chemical consumption in the course of leaching. In the study using hydrometallurgical methods; the leaching studies with Çukuralan ore, the optimum parameters were observed at a 40% solid/liquid ratio and 300 mg/l Jin Chan concentration, and gold was recovered with a yield of 90.89%. Hereby, Jin Chan consumption was 0.72 kg/t. In NaCN, on the other hand, the optimum parameters were achieved at a solid/liquid ratio of 40% and a concentration of 300 mg/l NaCN, and gold was obtained with a yield of 91.98%. NaCN consumption was 0.31 kg/t. In the leaching studies with Kaymaz ore, the optimum parameters were reached at 40% solid/liquid ratio and 300 mg/l Jin Chan concentration, and gold was recovered with an 81.55% yield. Jin Chan chemical consumption is seen at 1.27 kg/t. In NaCN, on the other hand, the optimum parameters were achieved at a solid/liquid ratio of 40% and a concentration of 300 mg/l NaCN, and gold recovery was achieved with a yield of 82.86%. NaCN consumption is calculated at 0.95 kg/t.

Pengaruh Variasi Bahan Aditif Pada Base Quench Medium dan Holding Time Tempering Terhadap Sifat Mekanik Material Roda Gigi

Gears are one of the most important components in various machine systems, and in their use, the gears rub and press against each other with other components, so they often experience wear on their surfaces. Therefore, to overcome these problems, the gear material is given a hardening and tempering heat treatment to improve its mechanical properties. The purpose of this study was to determine the effect of variations in cooling media in the quenching process and tempering holding time on the hardness value and impact strength of S45C steel. The method used is S45C steel heated at 950°C for 35 minutes, then cooled using water + 0.12% activated carbon, a 5% NaCl solution, and SAE 15 W 40 oil + 0.12% activated carbon. After that, it was tempered at 260 °C for 15 minutes, 25 minutes, and 35 minutes. Then a hardness test was carried out to determine the hardness value, and an impact test was carried out to determine the toughness value. From the results of the study, it was found that the optimum parameters for overcoming wear problems on gears were using water + 0.12% activated carbon cooling media and a tempering holding time of 15 minutes. From these optimum parameters, it produces a high hardness value of 36.3 HRC and an impact price of 0.23 J/mm².