Estimation of heat transfer coefficient of forced-air cooling and its experimental validation in controlled processing of forgings

Estimation of the cooling efficiency of an accelerated air for the needs of cooling of die forgings is presented. Temperature dependence of heat transfer coefficient (HTC) was calculated for different cooling conditions varied by airflow velocity, covering the range from 18 to 48?m/s. Time–temperature measurements performed on a full-scale semi-industrial cooling line provided similarity to conditions typical of industrial conveyor, which gives the results utilitarian significance in design of controlled processing (of steel forged products). Acquired HTC values, ranging from 164.7 to 298?W/m²?·?K, were validated in numerical simulation of cooling complex-shape forgings and subject to experimental verification, indicating perfect agreement with physical measurements.     

Training neural networks on high-dimensional data using random projection

Pattern Analysis and Applications - Training deep neural networks (DNNs) on high-dimensional data with no spatial structure poses a major computational problem. It implies a network architecture...     

A Stochastic Petri Net-Based Model of the Involvement of Interleukin 18 in Atherosclerosis

Interleukin 18 (IL-18) is a proinflammatory and proatherogenic cytokine with pleiotropic properties, which is involved in T and NK cell maturation and the synthesis of other inflammatory cytokines and cell adhesion molecules. It plays a significant role in orchestrating the cytokine cascade, accelerates atherosclerosis and influences plaque vulnerability. To investigate the influence of IL-18 cytokine on atherosclerosis development, a stochastic Petri net model was built and then analyzed. First, MCT-sets and t-clusters were generated, then knockout and simulation-based analysis was conducted. The application of systems approach that was used in this research enabled an in-depth analysis of the studied phenomenon. Our results gave us better insight into the studied phenomenon and allow revealing that activation of macrophages by the classical pathway and IL-18-MyD88 signaling axis is crucial for the modeled process.     

In Silico Study on Tumor-Size-Dependent Thermal Profiles inside an Anthropomorphic Female Breast Phantom Subjected to Multi-Dipole Antenna Array

Electromagnetic hyperthermia as a potent adjuvant for conventional cancer therapies can be considered valuable in modern oncology, as its task is to thermally destroy cancer cells exposed to high-frequency electromagnetic fields. Hyperthermia treatment planning based on computer in silico simulations has the potential to improve the localized heating of breast tissues through the use of the phased-array dipole applicators. Herein, we intended to improve our understanding of temperature estimation in an anatomically accurate female breast phantom embedded with a tumor, particularly when it is exposed to an eight-element dipole antenna matrix surrounding the breast tissues. The Maxwell equations coupled with the modified Pennes’ bioheat equation was solved in the modelled breast tissues using the finite-difference time-domain (FDTD) engine. The microwave (MW) applicators around the object were modelled with shortened half-wavelength dipole antennas operating at the same 1 GHz frequency, but with different input power and phases for the dipole sources. The total input power of an eight-dipole antenna matrix was set at 8 W so that the temperature in the breast tumor did not exceed 42 °C. Finding the optimal setting for each dipole antenna from the matrix was our primary objective. Such a procedure should form the basis of any successful hyperthermia treatment planning. We applied the algorithm of multi for multi-objective optimization for the power and phases for the dipole sources in terms of maximizing the specific absorption rate (SAR) parameter inside the breast tumor while minimizing this parameter in the healthy tissues. Electro-thermal simulations were performed for tumors of different radii to confirm the reliable operation of the given optimization procedure. In the next step, thermal profiles for tumors of various sizes were calculated for the optimal parameters of dipole sources. The computed results showed that larger tumors heated better than smaller tumors; however, the procedure worked well regardless of the tumor size. This verifies the effectiveness of the applied optimization method, regardless of the various stages of breast tumor development.     

Optimization of reinforcement layout of scissor‐type bridge using differential evolution algorithm

Scissors mechanisms are commonly used in safety engineering during the construction of temporary structures, owing to their inherent advantages of foldability, transformability, and reusability. We effectively utilized these scissors mechanism features to develop a lightweight, deployable emergency Mobile Bridge (MB) based on optimization, and control of the folding structure. Here, we discuss the problems of optimal reinforcement layout for the MB by formulating and solving three optimization problems, namely: (a) the load capacity maximization problem, (b) the weight minimization problem, and (c) coupling the load capacity maximization problem and the weight minimization problem. The potential benefits resulting from the application of reinforcement were evaluated using a combination of finite element analysis and an optimization algorithm based on the differential evolution method. The results demonstrate the significant positive influence of the additional reinforcing members. In particular, the limit load was increased by over 10 times, while the weight was decreased to approximately half. The proposed methodology enabled the development of a substantially improved version of the MB characterized by a higher load capacity and lower weight in comparison to the initial bridge design.     

Gas‐phase removal of indoor volatile organic compounds and airborne microorganisms over mono‐ and bimetal‐modified (Pt,Cu, Ag) titanium(IV) oxide nanocomposites

The photocatalytic deactivation of volatile organic compounds and mold fungi using TiO₂ modified with mono‐ and bimetallic (Pt, Cu, Ag) particles is reported in this study. The mono‐ and bimetal‐modified (Pt, Cu, Ag) titanium(IV) oxide photocatalysts were prepared by chemical reduction method and characterized using XRD, XPS, DR/UV‐Vis, BET, and TEM analysis. The effect of incident light, type and content of mono‐ and bimetallic nanoparticles deposited on titanium(IV) oxide was studied. Photocatalytic activity of as‐prepared nanocomposites was examined in the gas phase using LEDs array. High photocatalytic activity of Ag/Pt‐TiO₂ and Cu/Pt‐TiO₂ in the reaction of toluene degradation resulted from improved efficiency of interfacial charge transfer process, which was consistent with the fluorescence quenching effect revealed by photoluminescence (PL) emission spectra. The photocatalytic deactivation of Penicillium chrysogenum, a pathogenic fungi present in the indoor environment, especially in a damp or water‐damaged building using mono‐ and bimetal‐modified (Pt, Cu, Ag) titanium(IV) oxide was evaluated for the first time. TiO₂ modified with mono‐ and bimetallic NPs of Ag/Pt, Cu, and Ag deposited on TiO₂ exhibited improved fungicidal activity under LEDs illumination than pure TiO₂.     

Efficiency optimisation of the thermal energy storage unit in the form of the ceiling panel for summer conditions

The thermal energy storage unit in the form of the ceiling panel made of the gypsum‐microencapsulated phase change material composite with internal U‐shaped channels was optimised applying previously developed 1D‐3D numerical simulator. Calculations were carried out for variable inlet velocities of air, different properties of the composite expressed by enthalpy‐temperature curves, and summer climatic conditions in Central Poland (Warsaw). Optimal working temperature ranges of the composite were determined. Moreover, studies showed that for Central Poland, composites with wide ranges of the working temperature are preferred due to significant daily variations of ambient temperature during the whole summer.     

Performance indices of a common rail-system CI engine powered by diesel oil and biofuel blends

Conventional fuels used for supplying internal combustion piston engines include petrols and diesel oils produced from petroleum. These are a non-renewable energy source. The environmental policy of the European Union is geared towards increasing the share of renewable fuels in the overall energy consumption. An alternative fuel originating from a renewable source, which could be used for feeding self-ignition internal combustion engines are the fatty acid methyl esters (FAME) of plant oils. The paper reports selected results of testing a 1.3 MULTIJET SDE 90 PS self-ignition engine with the Common Rail reservoir feed system supplied with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME). Tests were carried out on an engine test bed equipped with an eddy-current brake. The purpose of the tests was to determine the economic–energy and ecological indices of engine operation. The concentrations of exhaust gas gaseous components were measured using a MEXA-1600DEGR analyzer, while the particulate concentrations, with a MEXA-1230PM analyzer. In addition, the variations of working medium pressures in the engine chamber and of fuel pressure upstream the injector were recorded as a function of crankshaft rotation angle using the AVL IndiSmart 612 indication system for this purpose. The physicochemical properties of fuels used in the tests were determined using a fuel analyzer. The obtained testing results made it possible to determine and assess the operation indices of the engine fed with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME) with slightly higher ester contents than the requirements of the currently applicable diesel oil standard.