Nanotransformations of a blanket at the fair dimensional combined processing with imposing of electric field the tool in the form of untied metal granules are considered. An object of researches are the figurine details applied in aviation, the missile and space equipment and in the oil and gas industry: driving wheels and a flowing part of cases of turbo-pump units, screws, krylchatka where there are sites of variable curvature with limited access of the tool in a processing zone.It is shown that the combination in the combined process of two-component technological environments of current carrying granules and the electroconductive liquid environment given with a high speed to a processing zone allows to receive the required quality of a blanket; action of electric field from a source with the increased tension allows to create at fair dimensional processingthe required peening from blows of firm granules. It gives the chance to raise a resource and durability of responsible knots of the aerospace equipment and oil and gas equipment, to expand the field of use of the combined processing with untied granules on a detailwith the sitesnot available to processing by a profile electrode.

Atom transfer radical polymerization (ATRP) is a kind of controllable reactive radical polymerization method with potential application value. The modification of graphene oxide (GO) by ATRP reaction can effectively control various graft polymer molecules Chain length and graft density, giving GO different functionality, such as good solvent dispersibility, environmental sensitive stimulus responsiveness, biocompatibility, and the like. In this paper, ATRP reaction and GO surface non-covalent bonding ATRP polymer molecular chain were directly initiated from GO surface immobilization initiator. The ATRP reaction modified GO was reviewed, and the process conditions and research methods of ATRP modification reaction were summarized, as well as pointed out the functional characteristics and application prospect of GO functionalized composites.

Polymer waste drilling fluid has extremely high stability, and it is difficult to separate solid from liquid, which has become a key bottleneck problem restricting its resource recycling. This study aims to reveal the stability mechanism of polymer waste drilling fluid and explore the destabilization effect and mechanism of ultrasonic waste drilling fluid. Surface analysis techniques such as X-ray energy spectrum and infrared spectrum were used in combination with colloidal chemical methods to study the spatial molecular structure, stability mechanism, and ultrasonic destabilization mechanism of drilling fluid. The results show that the particles in the drilling fluid exist in two forms: uncoated particles and particles coated by polymers, forming a high molecular stable particle system. Among them, rock particles not coated by polymer follow the vacancy stability and Derjaguin-Landau-Verwey-Overbeek (DLVO) stability mechanism, and the weighting material coated by the polymer surface follows the space stability and DLVO stability mechanism. The results of ultrasonic destabilization experiments show that after ultrasonic treatment at 1000 W power for 5 min, coupled with the addition of 0.02% cationic polyacrylamide, the dehydration rate is as high as 81.0%, and the moisture content of the mud cake is as low as 29.3%, achieving an excellent solid-liquid separation effect. Ultrasound destabilizes polymer waste drilling fluid by destroying the long-chain structure of the polymer. This study provides theoretical support and research direction for the research and development of polymer waste drilling fluid destabilization technology.

Global energy agencies and commissions report a sharp increase in energy demand based on commercial, industrial, and residential activities. At this point, we need energy-efficient and high-performance systems to maintain a sustainable environment. More than 30% of the generated electricity has been consumed by HVAC-R units, and heat exchangers are the main components affecting the overall performance. This study combines experimental measurements, numerical investigations, and ANN-aided optimization studies to determine the optimal operating conditions of an industrial shell and tube heat exchanger system. The cold/hot stream temperature level is varied between 10 ℃ and 50 ℃ during the experiments and numerical investigations. Furthermore, the flow rates are altered in a range of 50–500 L/h to investigate the thermal and hydraulic performance under laminar and turbulent regime conditions. The experimental and numerical results indicate that U-tube bundles dominantly affect the total pumping power; therefore, the energy consumption experienced at the cold side is about ten times greater the one at the hot side. Once the required data sets are gathered via the experiments and numerical investigations, ANN-aided stochastic optimization algorithms detected the C10H50 scenario as the optimal operating case when the cold and hot stream flow rates are at 100 L/h and 500 L/h, respectively.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

Paraffin wax is the most common phase change material (PCM) that has been broadly studied, leading to a reliable optimal for thermal energy storage in solar energy applications. The main advantages of paraffin are its high latent heat of fusion and low melting point that appropriate solar thermal energy application. In addition to its accessibility, ease of use, and ability to be stored at room temperature for extended periods of time, Nevertheless, improving its low thermal conductivity is still a big, noticeable challenge in recently published work. In this work, the effect of adding nano-Cu₂O, nano-Al₂O₃ and hybrid nano-Cu₂O-Al₂O₃ (1:1) at different mass concentrations (1, 3, and 5 wt%) on the thermal characteristics of paraffin wax is investigated. The measured results showed that the peak values of thermal conductivity and diffusivity are achieved at a wight concentration of 3% when nano-Cu₂O and nano-Al₂O₃ are added to paraffin wax with significant superiority for nano-Cu₂O. While both of those thermal properties are negatively affected by increasing the concentration beyond this value. The results also showed the excellence of the proposed hybrid nanoparticles compared to nano-Cu₂O and nano-Al₂O₃ as they achieve the highest values of thermal conductivity and diffusivity at a weight concentration of 5.0 wt%.