Effect of Grit Blasting Parameters on Surface and Near-Surface Properties of Different Metal Alloys

Ghara, Tina; Paul, S.; Bandyopadhyay, P.P.

doi:10.1007/s11666-020-01127-1

Cited by 24 publications

(9 citation statements)

References 38 publications

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“…In contrast, bacteria colonies are observed on the surfaces of the as-received copper and Cu SSP samples. The shot peening process results in variable surface grain refinement and treated affected zone depending on the peening coverage, peening material, and peening intensities [12]. Grain refinement intensifies with increasing the surface coverage and peening intensities and therefore increases the local hardness [16].…”

Section: Resultsmentioning

confidence: 99%

“…Grain refinement intensifies with increasing the surface coverage and peening intensities and therefore increases the local hardness [16]. The peening parameters were chosen so that the Cu SSP sample would have fine grains at the surface and near-surface with different induced surface roughness in comparison with SLSP 1 and SLSP 2 [11,12,16]. Copper-coated samples (CGDS SST) have a fine microstructure due to the fine grain characteristic of the feedstock powder used.…”

Section: Resultsmentioning

confidence: 99%

“…Surface modification techniques, such as surface nanocrystallization (SNC), have also been used to the same end. Nanograins can be produced at the surface by plastic deformation with processes such as mechanical grinding, grit blasting and shot peening [5][6][7][8][9][10][11][12]. Cold spray and SNC studies involve changes in surface roughness in addition to reduced grain size.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhanced Antibacterial Properties of Copper Surfaces Using Cold Spray Shot Peening

Razavipour

Singh

Jodoin

et al. 2021

International Thermal Spray Conference

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Metal surface characteristics play a significant role in interacting with their biological environment. Copper surfaces have been identified for their antimicrobial properties. Improvement of antibacterial and antiviral performances can be tailored by surface microstructure modification. Severe plastic deformation is an effective surface modification procedure to improve the mechanical performance of metal surfaces. This technique can be adapted to obtain surface grain refinement and induce surface roughness. In this work, cold spray shot peening is used to modify copper substrate surfaces and study the effects on their antibacterial properties. To modify the grain structure of copper, different shot-peening parameters were examined. The surface roughness and microstructure were investigated by employing optical and scanning electron microscopy. The bactericidal activity of copper substrates after shot peening treatment is discussed and a comparison between the bacterial load on treated (shot-peened surface and cold sprayed copper coating) and untreated surfaces (as-received) is provided. Testing of the surfaces after their exposure to the biological environment demonstrated improved microbial inactivation performances for surfaces that had undergone grain refinement without exceeding a certain roughness value.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhanced Antibacterial Properties of Copper Surfaces Using Cold Spray Shot Peening

Razavipour

Singh

Jodoin

et al. 2021

International Thermal Spray Conference

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show abstract

“…For making deformations, hardening includes blasting [5], magnetic-pulse processing [6], hardening by explosion [7], smoothing and rolling [8], and ultrasonic treatment [9]. Each hardening processing method based on the deformation effect on the cutting tool has the following characteristics: mechanics of deformation, specific features of formation of geometrical and physical-mechanical properties of the surface layer, and the process conditions.…”

Section: Introductionmentioning

confidence: 99%

Impact of Magnetic-Pulse and Chemical-Thermal Treatment on Alloyed Steels’ Surface Layer

et al. 2022

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The relevant problem is searching for up-to-date methods to improve tools and machine parts’ performance due to the hardening of surface layers. This article shows that, after the magnetic-pulse treatment of bearing steel Cr15, its surface microhardness was increased by 40–50% compared to baseline. In this case, the depth of the hardened layer was 0.08–0.1 mm. The magnetic-pulse processing of hard alloys reduces the coefficient of microhardness variation from 0.13 to 0.06. A decrease in the coefficient of variation of wear resistance from 0.48 to 0.27 indicates the increased stability of physical and mechanical properties. The nitriding of alloy steels was accelerated 10-fold that of traditional gas upon receipt of the hardened layer depth of 0.3–0.5 mm. As a result, the surface hardness was increased to 12.7 GPa. Boriding in the nano-dispersed powder was accelerated 2–3-fold compared to existing technologies while ensuring surface hardness up to 21–23 GPa with a boride layer thickness of up to 0.073 mm. Experimental data showed that the cutting tool equipped with inserts from WC92Co8 and WC79TiC15 has a resistance relative to the untreated WC92Co8 higher by 183% and WC85TiC6Co9—than 200%. Depending on alloy steel, nitriding allowed us to raise wear resistance by 120–177%, boriding—by 180–340%, and magneto-pulse treatment—by more than 183–200%.

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“…However, the proposed control index does not form a system, the actual smooth blasting control process is greatly influenced by human subjectivity, and the accuracy and reliability of the control is poor. Numerous domestic scholars have also conducted extensive research on the tunnel smooth blasting quality control, which mainly involves the repeated test and optimization of blasting parameters [1][2][3][4][5][6][7][8][9][10][11][12], neural network models [13,14], mutation comprehensive evaluation theory [15], computer simulation [16,17], information construction [18,19], three-dimensional laser scanning [20], and other technologies, thereby proposing a reasonable control technology. However, no unified system exists for studying the tunnel smooth blasting control index, control criterion, and control method.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Control of Smooth Blasting Quality in Rock Tunnels Using BP-ANN, ENN, and ANFIS

et al. 2021

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The construction quality of tunnel smooth blasting is difficult to control and fluctuates greatly. Moreover, the existing technology, which relies on the visual observation, empirical judgment, and artificial control, has difficulty meeting the requirements of tunnel smooth blasting construction quality control. This paper presents the construction principle of a tunnel smooth blasting quality control system, introduces a process quality control technology into quality control of tunnel smooth blasting construction, designs a framework for the tunnel smooth blasting quality control system, and collects control index data based on field investigation, expert consultation, and experimental research. By using the methods of index utilization rate statistics, gray correlation analysis, and principal component analysis, this paper primarily elects and selects the control indexes; establishes the tunnel smooth blasting quality control index system; constructs a comprehensive optimization control model of tunnel smooth blasting quality using back propagation artificial neural network (BP-ANN), Elman neural network (ENN), and adaptive neuro fuzzy inference systems (ANFIS); and studies the tunnel smooth blasting quality control system. The following are the conclusions of this study: (1) This paper presented a method of constructing a tunnel smooth blasting quality control index system and established this system with seven criteria layers, namely, geological conditions, explosive properties, borehole parameters, charge parameters, method of initiation, tunnel parameters, and construction factors, as well as a total of nine indexes. (2) The comprehensive optimization control model of BP-ANN, ANFIS, and ENN for tunnel smooth blasting quality was established. (3) The uniform design method was used to optimize the blasting parameters of the tunnel section, which needs to be controlled, and verify that the construction of these comprehensive optimization control models can change the focus of tunnel smooth blasting quality control from the traditional single index control method into a dynamic, intelligent, pluralistic, and integrated control technology.

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Effect of Grit Blasting Parameters on Surface and Near-Surface Properties of Different Metal Alloys

Cited by 24 publications

References 38 publications

Enhanced Antibacterial Properties of Copper Surfaces Using Cold Spray Shot Peening

Enhanced Antibacterial Properties of Copper Surfaces Using Cold Spray Shot Peening

Impact of Magnetic-Pulse and Chemical-Thermal Treatment on Alloyed Steels’ Surface Layer

Intelligent Control of Smooth Blasting Quality in Rock Tunnels Using BP-ANN, ENN, and ANFIS

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