РАЗРАБОТКА ЭНЕРГОСБЕРЕГАЮЩЕГО ИЗМЕЛЬЧИТЕЛЯ КОРМОВ

The various operational parameters and geometrical characteristics have a significant impact on how well the Proton Exchange Membrane Fuel Cell (PEMFC) performs. Cell temperature, back pressure, anode and cathode inflow velocities, Gas Diffusion Layer (GDL) porosity and thickness, cathode water mass percentage, flow channel dimensions, rib width, and porous electrode thickness are among the operating and design parameters that are optimized in this article. Using the traditional orthogonal array Taguchi approach, the optimization of design and operating parameters in software was done in two steps. From the preliminary analysis, it was concluded that rib width had the least impact on fuel cell performance and that back pressure had the greatest impact.

Modeling and optimization of gaseous helium (GHe) cooled high temperature superconducting (HTS) DC cables for high power density transmission

In the paper based on the Computational Fluid Dynamics (CFD) method three-dimensional flow fields are studied using FLUENT software. Sliding mesh method, RNG к - e turbulent model and second-order upwind difference scheme are used to perform the numerical simulation. Firstly, the prediction capabilities of the turbulence models used in the simulation are assessed in detail. Secondly, numerical study is focused on the velocity field of an actual quadrate stirred tank with a dual 45 degrees pitched four-blade turbine in given conditions of design and operation parameters. Finally, the influences of design and operation parameters on mixing effects are analyzed by the simulation of the turbulence intensity. The study provides reference aids for optimization of design and operation parameters.

Dynamic Simulation and Visualisation of pH-Modulated Fed-batch Fermentation for mAb Production from CHO Cell Cultures

To enhance desalination efficiency and reduce experimental costs, the development of advanced mathematical models for EMS is essential. In this study, we propose a novel hybrid approach that integrates neural networks with high-accuracy numerical simulations of electroconvection. Based on dimensionless similarity criteria (Reynolds, Péclet numbers, etc.), we establish functional relationships between critical parameters, such as the dimensionless electroconvective vortex diameter and the plateau length of current-voltage curves. Training datasets were generated through extensive numerical experiments using our in-house developed mathematical model, while multilayer feedforward neural networks with backpropagation optimization were employed for regression tasks. The resulting AI (artificial intelligence)-driven hybrid models enable rapid prediction and optimization of EMS design and operating parameters, reducing computational and experimental costs. This research is situated at the intersection of membrane science, artificial intelligence, and computational modeling, forming part of a broader foresight agenda aimed at developing next-generation intelligent membranes and adaptive control strategies for sustainable water treatment. The methodology provides a scalable framework for integrating physically based modeling and machine learning into the design of high-performance electromembrane systems.

Economic design of a rock bed storage device for storing solar thermal energy

Optimization of design and operation parameters for hybrid ground-source heat pump assisted with cooling tower

Using a gradient optimization method with objective functions formulated in terms of a signal-to-noise ratio (SNR) calculated at given values of the prescribed spatial ground resolution, optimization problems of geometrical parameters of a distributed optical system and a charge-coupled device of a space-based optical-electronic system are solved for samples of the optical systems consisting of two and three annular subapertures. The modulation transfer function (MTF) of the distributed aperture is expressed in terms of an average MTF taking residual image alignment (IA) and optical path difference (OPD) errors into account. The results show optimal solutions of the optimization problems depending on diverse variable parameters. The information on the magnitudes of the SNR can be used to determine the number of the subapertures and their sizes, while the information on the SNR decrease depending on the IA and OPD errors can be useful in design of a beam combination control system to produce the necessary requirements to its accuracy on the basis of the permissible deterioration in the image quality.

Enhancing powder coating classification accuracy via mesh-modified classifier design and operational parameter optimization

Work purpose: the investigation of transport process safety in construction industry of the Bryansk region, the substantiation of reasons, factors and circumstances of accidents in the construction companies of the region, the substantiation of the impact of hydraulic drive unit failures upon safety of transport construction machinery with the hydraulic drive with the purpose of driver safety. Investigation problem: on the basis of the obtained results of the safety investigations of transport processes, reasons defined, revealed injury factors of drivers during the operation of the load flat car hydraulic drive of transport means to develop motion parameters of the “hydraulic drive-load flat car” system which will not allow arising oscillations of the system resulting in hydraulic drive failure arising which has influence upon driver’s work safety. The investigations were carried out on the basis of a system analysis of accident examinations in the regional construction industry which on the basis of statistical data allows the defining safety state of transport construction machinery. By means of investigations it is defined that 90% of transport construction machines are equipped with a hydraulic drive. In the hydraulic drive the most significant element is a hydraulic cylinder – the most loaded element performing all basic operations of a working process of loading and unloading. In the hydraulic drive there is used a telescopic hydraulic cylinder in which during operation there are revealed design-production defects (DPD) which result in injury of machine service personnel. One of DPD manifestations is oscillation formation in the hydraulic drive which results in the destruction of hydraulic cylinder attachment fitting. It is defined that the support of hydraulic drive reliability and safety is a difficult problem which needs a complex solution still at designing and creation, and during the operation. The complexity of the problem causes the necessity of design and operation parameter optimization, in the first place, that of an executing hydraulic cylinder of the hydraulic drive with the use of mathematical modeling. The review of the mathematical modeling methods of hydraulic cylinder parameters allows drawing the conclusion that the existing methods have many assumptions and do not allow creating completely reliable and safe transport construction engineering. The investigation novelty consists in the offered procedure for the solution of motion equations of the “hydraulic drive – load flat car” system which allows calculating the motion system parameters, defining the development of system oscillation above critical able to destruct a fitting unit of the hydraulic cylinder to the load flat car. Conclusion. The algorithm offered for the solution of mathematical equations allows making a conclusion on the stability and safety of the “hydraulic cylinder – load flat car” system, finding optimum values of motion parameters at any time moment of a transitional process.

Experiments were conducted to determine the effects of blade angle and cutting angle on the cutting force of litchi stalk, which are important in cutter design and operational parameter optimization, and to compare the maximum cutting forces for V-cutters and for unilateral V-cutters. Five blade angles (15, 22.5, 30, 45, and 60) and four cutting angles (0, 30, 45, and 60) were selected for the experiments. The maximum cutting force for V-cutters increased with blade angle. However, as cutting angle was 0, 30, 45, and 60, no significant trend between maximum cutting force and blade angle could be found for unilateral V-cutters. The maximum cutting force reduced with cutting angle for both V-cutters and unilateral V-cutters; however, such effect was not significant. For the four cutting angles and the five blade angles( except for 15) , all had maximum cutting forces for unilateral V-cutters that were on average less than those for V-cutters.

Electromagnetic launching mass driver system (projectile) has been examined and evaluated as an eligible alternative to the chemical propulsion systems, in space transportation. The projectile has been arranged to reach to its orbital speed at delivered altitude, with an energy transferred externally to a projectile all the flyway through the electromagnetic launcher. The multistage electromagnetic launcher structure contains the capacitors for storing energy and transfers this energy through a switching inductor to a mass driver. The mass driver is synchronously being energized by a voltage through an oscillating coil-capacitor circuit. This paper presents dependence and optimization of design and performance parameters of coilgun equations. Cost estimations of electromagnetic launching system are also calculated in energy per unit mass.

In this work, a method is developed for the component design of chassis bushings with contoured inner cores, aided by artificial neural networks (ANNs) and design optimization. First, a model of a physical chassis bushing is generated using the finite element method (FEM). To determine the material parameters of the material model, a material parameter optimization is conducted. Based on the bushing model, different samples for a design study are generated using the design of experiments method. Due to invalid areas of the geometrical model definitions, constraints are established and the design parameter space is cleaned up. From the cleaned design parameter space, a database of several design parameter samples and three associated quasi-static stiffnesses, calculated with FEM simulations, is generated. The database is subsequently used for the training and hyper-parameter optimization of the ANN. Subsequently, the feed-forward ANN is employed in a design study, where stiffnesses are prescribed and design parameters identified. The design process is inverted with the help of a constrained design parameter optimization (DO), based on particle swarm optimization (PSO). Two usecases are defined for the evaluation of the design accuracy of the entire method. The design parameters found are validated by corresponding FEM simulations.

Industrial sludge is a by-product which is enormously generated in wastewater treatment plants. Constructed wetland for sludge treatment (CWST) is a low cost, effective technology. This study investigated the effect of various design and operation parameters on the efficiency of four pilot-scale CWSTs to determine the optimal parameters by using the Analytic Hierarchy Process (AHP) for Decision- Making. The wetland units were planted with Phragmites australis or Typha angustifolia, operated with four sludge loading rate (SLR) (50, 60, 70 and 80 L/m2) and monitored in six different hydraulic retention time (HRT) (2,5,7,9,12 and 14 days). AHP results provided the optimal key parameters (vegetation of P. australis, 14-day HRT, SLR of 60 L/m2) which gave the most effective sludge treatment, reducing 99.8%, 95.16% and 98.23% for COD, TKN and TP, respectively. The results also showed that HRT, SLR and vegetation remarkably affected to the efficiency of CWST. In addition, AHP is an effective method to determine the optimal design and operation parameters of CWST.

Performance enhancement of up-flow anaerobic sludge blanket reactor for psychrophilic temperature during the dry season: Kality wastewater treatment plant