<4D6963726F736F667420576F7264202D20DAC8C7D320E6E1EDCB20E6E6D3C7E320312D3132> Al-Khwarizmi Engineering Journal Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, June , (2019) P.P. 1- 12 Effect of Quenching Media Variations on the Mechanical Behavior of Martensitic Stainless Steel Abbas Kh. Hussein* Laith K. Abbas** Wisam N. Hasan*** *, **Department of Materials Engineering /University of Technology/ Baghdad / Iraq ***Kut Technical Institute/ Middle Technical University / Baghdad/ Iraq *Email: www.Abbas2000x@gmail.com **Email: www.laithKa2012@gmail.com ***Email: www.weeesam1982@yahoo.com (Received 24 June 2018; accepted 4 November 2018) https://doi.org/10.22153/kej.2019.11.002 Abstract The purpose of this study is designate quenching and tempering heat treatment by using Taguchi technique to determine optimal factors of heat treatment (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time) for increasing hardness, wear rate and impact energy properties of 420 martensitic stainless steel. An (L18) orthogonal array was chosen for the design of experiment. The optimum process parameters were determined by using signal-to-noise ratio (larger is better) criterion for hardness and impact energy while (Smaller is better) criterion was for the wear rate. The importance levels of process parameters that effect on hardness, wear rate and impact energy properties were obtained by using analysis of variance which applied with the help of (Minitab18) software. The variables of quenching heat treatment were austenitizing temperature (985 C˚,1060 C˚),a soaking times (50,70 and 90 minutes) respectively, Percentage of volumetric fractions of nanoparticles with three different levels(0.01, 0.03 and 0.08 %) were prepared by dispersing nanoparticles that are (α-Al2O3,TiO2 and CuO) with base fluids (De-ionized water, salt solution and engine oil).The specimens were tempered at 700°C after quenching of nanofluids for (2 hours).The results for ( S/N) ratios showed the order of the factors in terms of the proportion of their effect on hardness, and wear rate properties as follow: Austenitizing temperature ( 1060 C˚),Type of base media (salt solution), Nanoparticles type (CuO), Percentage of nanoparticles (0.08%) and Soaking time(90min) was the least influence while for the impact energy were as follows: Type of base media (oil), Austenitizing temperature (985C˚), Percentage of nanoparticles (0.01%), Nanoparticles type (α-Al2O3) and last soaking time (50min). Keywords: Nanofluids, quenching, hardness, wear, impact energy, Taguchi technique. 1. Introduction Martensitic stainless steels occupy a unique status as engineering materials by virtue of their excellent combination of properties. These steels find extensive application in chemical plants, power generation equipments and many other applications [1,2]. Unlike other types of stainless steels, the properties of martensitic stainless steels are greatly modified by normal heat treatment procedures [3,4]. To enhance heat transfer to meet the cooling challenge necessary. New type of quenching media has been developed, it is called nanofluids [5]. Nanofluid is a fluid containing nanometer-sized particles, called nanoparticles. These fluids are engineered colloidal suspensions of nanoparticles with sizes typically of the order of (1-100 nm) in a base fluid. Choi in 1995 coined the term nanofluids for this new class of heat transfer fluids [6,7]. The nanoparticles used in nanofluids are typically made of metals, oxides, carbides, or carbon nanotubes. Nanofluids have novel properties that make them potentially useful in many applications in heat transfer. Nanofluids Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 2 show improved stability compared to the conventional fluids added with micrometer or millimeter-sized solid particles because of its size effect and Brownian motion of the nanoparticles in liquids [8].Possible reasons of discrepancy in experimental data Attributed to the complexity of correlations between nanofluid parameters such as material , concentration, size and shape of nanoparticles and properties as density, pH value and thermal conductivity to obtain on the better type of nanofluids as well as many of heat treatment parameters to get optimum structural material for desired application. This study investigated with the Taguchi method to optimize 420 martensitic stainless steel heat treatment process parameters, austenitizing temperature, percentage of nanoparticles, type of base media, type of nanoparticles and soaking time to get the better hardness, wear and impact energy properties. 2. Experimental Procedure 2.1. Materials The following materials were used in the nanofluids synthesis because of its good thermal properties: Nano titanium dioxide (TiO2) powder, nano aluminum oxide(α-Al2O3) powder and copper oxide (CuO) nanoparticle (supplied by Zhengzhou Dongyao nano materials Co.LTD.). The properties of these nanoparticles are given on table (1). Those materials were added to base media (Deionized water, Salt solution (NaCl+water) and Engine oil). Sodium lauryl sulphate as surfactant was used. Table1, Physical properties of nanoparticles. Color Crystal form Density(g/cm3) Volume density (g/cm3) Specific surface area (m2/g) Purity (%) APS (nm) Nanoparticle material white γ 3.91 0.916 160.1 >99.99 50 α-Al2O3 white Cube 3.9 0.25 220 >99.9 20 TiO2 black Sphere 6.4 0.30-0.45 120 >99.9 50 CuO 2.2. Nanofluid Preparation In this research, eighteen types of nanofluid are prepared [(Al2O3/ Deionized water), (Al2O3/ salt solution), (Al2O3/ engine oil)], [(TiO2/ De ionized water),(TiO2/ salt solution), (TiO2/ engine oil)], [(CuO/ De ionized water), (CuO / salt solution), (Cuo / engine oil)] with volume fractions of (0.01, 0.03 and 0.08%).In this paper nanofluid was prepared by two step method where the given nanoparticle is mixed to the base fluid to obtain suspension. Law of mixtures was employed to determination quantity of nanoparticles wanted for preparation of nanofluids. The mass of nanoparticles (Mp) and base fluid (Mf) are measured with balance of (0.0001 g) an accuracy. The weight percentage (ϕ) can be calculated by using Eq (1). ϕ = ���/��� ��� �� ��� ��� … (1) Where: Φ: volume fraction. Mnp: mass of nanoparticle(g). ρnp: density of the nanoparticle(g/L). Mbf: mass of the base fluid (g). ρbf: density of the base fluid(g/L) [9]. A mechanical stirrer was used to achieve a homogenously dispersed solution. This method was based on Han and Rhi (2011) [10] and Mahendran et al., (2012), [11]. After preparing the proper mix of the nanoparticles and fluids by mechanical stirrer, nanoparticles are dispersed in fluids using magnetic stirrer. During the process Sodium Dodecyl Sulphate (SDS) surfactant is added to the solution in proper proportions to ensure stability of nanofluid. For various purposes, sound energy is used to agitate the particles in nanofluid, this process is known as sonication. By breaking intermolecular interaction, sonication is also used for speed up the dissolution. Sonication is more useful when the magnetic stirring was not much effective for given sample. For nanoparticles which were not evenly dispersing in liquids, sonication is most preferable. The sonication process is achieved in two steps were: A- Initially Sonicate the mixture continuously for (30 min) with sonicator of frequency (40 KHz) to obtain uniform dispersion of nanoparticles in fluids, this process is achieved with ultrasonic mixer (LUC – 410(50 Hz,400W)). B-Sonicate the Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 3 mixture continuously for (90 min) with probe sonicator (model 300 VT ultrasonic homogenizer) of output frequency (20 KHz). 2.3. Material of the Research Specimens The 420 martensitic stainless steel samples were taken for this study. The chemical composition analysis of the specimens was carried out at the (Specialized Institute for Inspection and Engineering Qualifying/Iraq) by x-ray fluorescent. The chemical composition of the 420 martensitic stainless steel is shown in table (2). Table 2, The chemical composition of 420 martensitic stainless steel specimens. 2.4. Heat Treatment Process Eighteen types of heat treatment were performed, these were exhibited of Schedule (4). Quenching heat treatment was implemented to harden the 420 martensitic stainless steel. Quenching heat treatment includes heating of samples to austenitizing temperature in an electric furnace (carbolite cwf 1200 muffle furnace) where the samples was held at (985°C, 1060°C) of heating rate (7°C /min)with soaking times ( 50,70 and 90 min ) to ensure uniformity of temperature throughout the full volume to attain a identical structure of austenite, subsequently each group of samples were quenched in diverse quenching mediums (nanofluids) ,and finally tempered at (700°C) for (2)hours. 2.5. Wear and Hardness Properties Calibrated Vickers hardness measurements were performed on all the samples to determine the hardness of the martensitic stainless steel in each heat treatment condition. Results were reported as adjusted from five tests per sample. All of the procedures were carried out according to the (ASTM E92-82/E2) standard method. The wear resistance of martensitic stainless steel being studied was evaluated using a Pin-on-Disc Tribometer, according to the testing procedure outlined in (ASTM Designation G 99 - 95A). The specimens of same dimensions were grinded and polished used for both abrasive wear rate analysis and hardness testing. Dimensions of the specimen are (10mm × 10mm × 5mm). A parameter referred to as wear rate used to define the wear severity was calculated using Equation (2). W� = �� ��∗�� … (2) Where: WR= wear rate. ΔV= Volume loss of the specimen. Ss = Sliding distance (m). Fn = Normal load (N). [12] The wear test was carried out with constant sliding speed (200 rpm), time (10 min) and load (1٥ N) To find out the effect of the experiment parameters (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time). Wear tests are performed under dry nonlubricated condition and at ambient temperature of 25 °C. 2.6. Charpy Impact Test The charpy impact test of the quenched martensitic stainless steel sample was carried on JBS impact testing machine. The specimens were supported horizontally with the V-notch opposite to the strike end. The energy absorbed before fracture was then read directly on the digital gauge of machine. The Charpy V-notch test method has been standardized according to the (ASTM standard E23). 2.7. Microstructure Analysis The analysis of the microstructures gained for several variants of heat treatment was analyzed by using optical Microscopic. In preparation for examination under the optical microscope, the samples were finely polished and etched to expose the microstructure. A Villela etchant was chosen from the list of etchants in (ASTM E407-07) Standard Practice for Micro etching Metals and Alloys (ASTM International,2007). The determination of the phases present in the treated samples was carried out by X-ray diffractometry Element C% Si% Mn% P% S% Cr% Mo% Ni% Al% Cu% Fe% Composition % 0.279 0.519 0.348 0.029 0.01 12.64 0.065 0.14 0.005 0.055 Bal Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 4 (XRD) technique, using a Shimadzu (XDR7000) X-ray. 3. Taguchi Method The Taguchi method is a powerful tool for designing high quality systems based on orthogonal array experiments that provide much- reduced variance for experiments with an optimum setting of process control parameters [13,14]. The method has also been widely used in engineering analysis to optimize performance characteristics through design parameter settings. The Taguchi method is based on orthogonal arrays and analysis of variance (ANOVA) to minimize the number of experiments and to effectively improve product quality [14,15]. 4. Design of Experiment The experimental procedures include parameters (variables) and levels as shown in table (3) based on the Taguchi technique. Austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time, these are process parameters that considered for this study. In the present investigation an(L18) orthogonal array was chosen as shown in table (4). The experiments were performed based on the run order generated by Taguchi model. This analysis involve the rank based on the delta statistics, which equals the relative value of the effects. The experimental results were transformed into signal-to-noise ratio (S/N). The (S/N) ratio for the (hardness and impact energy) using "Larger the better" characteristics as for the wear property using "Smaller the better" characteristics, which can be calculated as logarithmic transformation of the loss function is given as: A.Larger the Better (LTB) � � = −10log101/n ∑[1/Y !] … (3) B. Smaller the Better (STB) � � = −10log10 ∑[Y ! /n] … (4) Where: Y: results of experiments, observations or quality, N: Number of trials of repetitions, S: the variance [16]. Table 3, Control factors and their levels. Unit Levels Control factors Symbol oC ----- 1060 985 Austenitizing temperature A ----- 0.08% 0.03% 0.01% Concentration media B ----- Engine oil Salt solution Deionized water Base media C ----- CuO TiO2 α-Al2O3 Nano particles type D min 90 70 50 Soaking time E 5. Results and Discussions 5.1. S/N Ratios Analysis The (S/N) ratio response was analyzed using the equation (3) for the hardness and impact energy while equation (4) using for wear rate, Figures (1,2,3) and table (5) shows the main effects plots of (S/N) ratios for hardness, wear and impact energy. From the figures (1,2,3) and table (5) it is evident that the order of factors by effect was as follows: Austenitizing temperature (1060C˚), Type of base media (salt solution), Nanoparticles type (CuO), Percentage of nanoparticles (0.08%) and Soaking time(90min) was the least influence while for the impact energy were as follows: Type of base media (oil), Austenitizing temperature (985C˚), Percentage of nanoparticles (0.01%), Nanoparticles type (α- Al2O3) and last soaking time (50min). Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 5 Table 4, Signal to Noise Ratios for the controlling factors considering Hardness, Wear rate and Impact energy. S/N - impact Energy Impact Energy (J) S/N- Wear Rate wear rate mm3/N.m S/N- hardness Hardness (HV) Parameters Exp.t E D C B A 35.707 61 130.881 2.86E-07 50.931 352 1 1 1 1 1 1 34.807 55 135.318 1.71E-07 52.75 434 2 2 2 1 1 2 34.964 56 134.23 1.94E-07 52.277 411 3 3 3 1 1 3 34.648 54 133.734 2.06E-07 52.063 401 2 1 1 2 1 4 34.151 51 139.755 1.03E-07 53.715 485 3 2 2 2 1 5 35.269 58 134.23 1.94E-07 52.277 411 1 3 3 2 1 6 34.151 51 135.318 1.71E-07 52.527 423 1 2 1 3 1 7 33.442 47 138.839 1.14E-07 53.46 471 2 3 2 3 1 8 35.269 58 134.23 1.94E-07 52.277 411 3 1 3 3 1 9 33.255 46 140.778 9.14E-08 53.962 499 3 3 1 1 2 10 34.486 53 138.839 1.14E-07 53.46 471 1 1 2 1 2 11 34.648 54 137.256 1.37E-07 52.987 446 2 2 3 1 2 12 33.442 47 144.86 5.71E-08 54.712 544 3 2 1 2 2 13 33.442 47 144.86 5.71E-08 54.712 544 1 3 2 2 2 14 34.964 56 135.318 1.71E-07 52.527 423 2 1 3 2 2 15 32.669 43 143.276 6.86E-08 54.453 528 2 3 1 3 2 16 32.869 44 143.276 6.86E-08 54.453 528 3 1 2 3 2 17 34.32 52 138.839 1.14E-07 53.46 471 1 2 3 3 2 18 35 4.29E-04 86 HRB (untreated) Table 5, Responses table for SN ratio-(Hardness, Wear rate and Impact energy). soaking time nanoparticles type type of base media percentage of nanoparticles Austenitizing temperature Hardness 52.89455189 52.61841352 53.10786924 52.72776842 52.47512277 Level 1 53.03988053 53.35842167 53.75835368 53.33422033 53.85840718 Level 2 53.5658625 53.52345973 52.634072 53.43830616 Level 3 0.671310612 0.905046212 1.124281686 0.710537741 1.383284414 Delta 5 3 2 4 1 Rank soaking time nanoparticles type type of base media percentage of nanoparticles Austenitizing temperature Wear Rate 137.1612949 136.046449 138.1410788 136.2169574 135.1706082 Level 1 137.2901705 138.5575413 140.1479454 138.7928115 140.8114511 Level 2 139.5216235 139.3690986 135.6840646 138.9633199 Level 3 2.360328665 3.322649534 4.46388082 2.74636247 5.640842898 Delta 5 3 2 4 1 Rank soaking time nanoparticles type type of base media percentage of nanoparticles Austenitizing temperature Impact Energy 34.56235025 34.65689387 33.97872639 34.64436004 34.71193002 Level 1 34.1963485 34.25332668 33.86619043 34.31925224 33.78830151 Level 2 33.99164854 33.84012675 34.90543048 33.78673501 Level 3 0.57070171 0.816767126 1.039240057 0.857625031 0.923628509 Delta 5 4 1 3 2 Rank Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 6 Fig. 1. Main effects plots for SN ratios-(Hardness). Fig. 2. Main effects plots for SN ratios- (Wear rate). Fig. 3. Main effects plots for SN ratios- (Impact energy). Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 7 5.2. ANOVA Analysis Analysis of variance (ANOVA) was used to analyze the influence of parameters (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time) on the hardness, wear rate and impact energy properties of 420 martensitic stainless steel. The (ANOVA) determines the relative significances of factors in expressions of their percentage contribution to the response[17].We can observe from the (ANOVA) analysis (Table(6) that the ranking of parameters according to its influence on the total variation on hardness, and wear rate properties were as follows: Austenitizing temperature, Type of base media, Nanoparticles type, Percentage of nanoparticles and Soaking time was the least influence while for the impact energy were as follows: Type of base media , Austenitizing temperature , Percentage of nanoparticles, Nanoparticles type and last soaking time . Table 6, Results of the (ANOVA). (Hardness, Wear rate and Impact energy). Hardness Source DF AdjSS Adj MS F-Value P-Value % of contribution A 1 23835 23834.7 171.76 1.09E-06 46.02506 B 2 4809 2404.5 17.33 0.0012372 9.286114 C 2 10804 5402 38.93 7.537E-05 20.86238 D 2 7116 3558.2 25.64 0.0003316 13.7409 E 2 4112 2056.2 14.82 0.0020416 7.940217 Error 8 1110 138.8 2.143395 Total 17 51787 100 Wear Rate Source DF AdjSS AdjMS F-value P-Value % of contribution A 1 3.16E-14 3.16E-14 135.07 2.74E-06 47.16418 B 2 6.4E-15 3.2E-15 13.61 0.002661 9.552239 C 2 1.23E-14 6.1E-15 26.26 0.000305 18.35821 D 2 1.03E-14 5.1E-15 21.98 0.000562 15.37313 E 2 4.6E-15 2.3E-15 9.8 0.007062 6.865672 Error 8 1.9E-15 2E-16 2.835821 Total 17 6.7E-14 100 Impact Energy Source DF AdjSS AdjMS F-value P-Value % of contribution A 1 133.39 133.389 88.11 0.0000136 28.96634 B 2 76 38 25.1 0.000357 16.5038 C 2 134.33 67.167 44.37 0.0000468 29.17047 D 2 70.33 35.167 23.23 0.0004657 15.27253 E 2 34.33 17.167 11.34 0.0046238 7.45494 Error 8 12.11 1.514 2.62975 Total 17 460.5 100 where: DF=Degree of Freedom, Seq SS=Sequential Sum of square, Adj SS=Adjacent Sum of Square, Adj MS=Adjacent mean Square, F=Fisher’s test. 5.3. Regression Equation A Regression model is developed using statistical software (MINITAB 18). Regressions equation make correlations correlations between the significant terms acquired from (ANOVA) analysis namely (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time). Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 8 Hardness (HV) = 458.50 - 36.39 A(oC )_985 + 36.39 A(oC )_1060 - 23.00 B(%)_0.01 + 9.50 B (%)_0.03 + 13.50 B(%)_0.08 - 0.67 C_Deionized water - 29.67 C_Engine oil + 30.33 C_Salt Solution + 18.83 D_CuO + 8.67 D_TiO2 - 27.50 D_α-Al2O3 - 13.17 E(min)_50 - 8.00 E(min)_70 + 21.17 E(min)_90 … (5) Wear= Rate 1.3969E-07+ 4.191E-08A(oC )_985 - 0.000000 A(oC )_1060+ 2.603E-08 B(%)_0.01 - 8.25E-09 B(%)_0.03 - 0.000000 B(%)_0.08+ 6.98E-09 C_Deionized water + 2.794E-08 C_Engine oil- 0.000000 C_Salt Solution - 1.968E-08 D_CuO - 1.397E-08D_TiO2+ 0.000000 D_α-Al2O3 + 1.651E-08 E(min)_50 + 5.08E-09 E(min)_70- 0.000000 E(min)_90 … (6) Impact= Energy 51.833 + 2.722 A(oC )_985 - 2.722 A(oC )_1060 + 2.333 B(%)_0.01 + 0.333 B(%)_0.03- 2.667 B(%)_0.08 - 1.500 C_Deionized water + 3.833 C_Engine oil - 2.333 C_Salt Solution - 2.333 D_CuO - 0.167 D_TiO2 + 2.500 D_α-Al2O3 + 1.833 E(min)_50 - 0.333 E(min)_70 - 1.500 E(min)_90 … (7) 5.4. Model Summary From the graphs (4-A,4-B,4-C) shows that the data closely follow the straight lines, denoting a normal distribution. Fig. 4. Normal probability plot of residuals: A-hardness, B-wear rate and impact energy of 420 stainless steel). Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 9 Also table (8) shows that (R2) approaches for this model very close to unity, and thus acceptable. It demonstrates that 97% approximately of the variability in the data can be explained by this model. Thus, this model provides reasonably good explanation of the relationship between the independent factors and the response. Table 7, Model summary of (Hardness, Wear rate and Impact energy). Hardness Wear Rate Impact Energy S 11.7798 1.53E-08 1.2304 R-sq 97.86% 97.21% 97.37% R-sq(adj) 95.44% 94.06% 94.41% R-sq(pred) 89.15% 85.86% 86.69% 5.5. Microstructural Analysis From the micrograph that shows in figure (7) of samples quenched at different quenchants medium and tempered at (700°C) for (2 hours), it is noted that a microstructure consisting of full martensitic matrix with different ratios of un dissolved carbide dependent on heat treatment variables (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time). Steels with more than (0.2%) carbon and (12- 13%) chromium content consist of different volumes of (M3C, M7C3, and M23C6) carbide precipitate [18]. In this investigation, only (M23C6) carbides can be said to be identified due to the austenitizing and tempering temperatures used. As it is shows of the micrograph that shown in Figure (7) and the(XRD) spectrum in figures (5,6) for samples austenitized at temperatures of (985 and 1060 °C) if we take it as examples of the heat treatments that were conducted, it clearly appears a reduction in intensity associated with a displacement to smaller angles. The peak displacement increases with increasing quenched temperature, showing the greater chromium carbides decomposition with temperature and the increased martensite saturation by carbon.Getting (M23C6) carbide as a final consequence and decreasing it with increase of austenitizing temperature this explains increasing in hardness and decrease wear rate that can be attributed to increment of both chromium and carbon content dissolved in the martensite[19,20]. Fig. 5. X-ray diffraction pattern of AISI420 martensitic stainless steel cooled of (0.08%α- Al2O3+engine oil) at 985 ºC for 90 min and tempered at (700°C) for (2 hours). Fig. 6. X-ray diffraction pattern of AISI 420 martensitic stainless steel cooled of (0.03% α- Al2O3+engine oil) at 1060 ºC for 70 min and tempered at (700°C) for (2 hours). Abbas Kh. Hussein Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 1- 12 (2019) 10 Fig. 7. Optical microstructure of the specimens rank from (1 to 18) according to design of experiment that shown in table (2). 6. Conclusions The approach of (Taguchi‘s) robust design method to study hardness, wear rate and impact energy for 420 martensitic stainless steel led to conclude the following: 1-The Taguchi method was successfully applied to determine the optimal values of austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time in order to maximize the hardness, impact energy and minimize wear rate. 2-The hardness value and impact energy value of the heat treated specimens were greater than that of untreated specimens and the wear rate was less for heat treated specimens. 3-From response table for (S/N ) ratio with respect to the hardness and wear rate we can marked on the most important factor where the ranking of factors as follows in terms of the proportion of their effect on hardness, and wear rate properties: Austenitizing temperature (1060C˚), Type of base media (salt solution), Nanoparticles type (CuO), Percentage of nanoparticles (0.08%)and Soaking time(90min) was the least influence while for the impact energy were as follows: Type of base media (oil), Austenitizing temperature (985C˚), Percentage of nanoparticles(0.01%), Nanoparticles type (α- Al2O3) and last soaking time (50min). 7. 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Salinas-Bravo," Effect of heat treatment on the stress corrosion cracking behaviour of 403 stainless steel in NaCl at 95°C," Materials letters, vol.43, no.4, pp.208-214,2000. )2019( 1- 12، صفحة 2د، العد15دجلة الخوارزمي الهندسية المجلم عباس خماس حسين 12 لصدأ مارتنسياتيلتأثير اختالف وسط التقسية على السلوك الميكانيكي لفوالذ مقاوم عباس خماس حسين* ليث قيس عباس** وسام ناجي حسن*** / الجامعة التكنولوجية/ العراق ** قسم هندسة المواد ,* /الجامعة التقنية الوسطى / العراق كوت / *** المعهد التقني www.Abbas2000x@gmail.com:البريد االلكتروني * www.laithKa2012@gmail.com:البريد االلكتروني ** www.weeesam1982@yahoo.com البريد االلكتروني: *** الخالصة (درجة المثلى للمعاملة الحرارية العوامل لتحديد تاغوتشي طة استخدام تقنيةاتصميم معاملة حرارية (اخماد ومراجعة) بوس هو الدراسة هذه من الغرض معدل البلى وطاقة ,الخواص (الصالدة لزيادة ) النقعنوع الجسيمات النانوية ووقت و نوع وسط األساسو النسبة المئوية للجسيمات النانوية االوستنايتحرارة لتصميم التجربة. عوامل العملية المثلى حددت باستخدام معيار )١٨L(تم اختيار مصفوفة متعامدة .٤٢٠المارتنسايتي أ الصدمة) لفوالذ مقاوم الصد )Signal/Noise( (األكبر هو األفضل) معيار بينماللصالدة وطاقة الصدمة )تم الحصول على مستويات األهمية البلى لمعدل كان) األفضل األصغر هو . الحرارية للمعاملة المتغيرات.)١٨(منتابباستخدام تحليل التباين المطبق بمساعدة برنامج معدل البلى وطاقة الصدمة,الصالدةخواص لعوامل العملية على للكسور الحجمية المئوية النسبة التوالي، على) دقيقة ٩٠ ، ٥٠،٧٠( النقع وأوقات ،) ˚١٠٦٠C ،˚C ٩٨٥( األوستنايت حرارة درجة (اخماد) كانت ) 3O2Al-α،2TiO،CuO) تم تحضيرها من خالل تشتيت جسيمات نانوية التي هي (%٠٫٠٨و٣٠٫٠،٠١،٠( بثالثة مستويات مختلفةللجسيمات النانوية أظهرت.لساعتين بعد االخماد بالموائع النانوية ˚C)٧٠٠( العينات بدرجةتم مراجعة بأوساط أساسية (الماء غير المتأين، محلول الملح، زيت المحرك). ١٠٦٠االوستنايت (درجة حرارة : تياال النحو وفق على الصالدة ومعدل البلى تأثيرها على الخواص نسبة حيث من العوامل ترتيب (S/N )النتائج لنسب C˚ ,()( نوع الجسيمات النانوية ,)محلول ملحينوع وسط االساسCuO(, )بينما )%0.08( النسبة المئوية للجسيمات النانوية واخيرادقيقة) ٩٠وقت النقع ، )3O2Al-α( نوع الجسيمات النانوية، )C˚٩٨٥االوستنايت (درجة حرارة ,)زيت المحركنوع وسط االساس( :تياال النحو وفقلطاقة الصدمة كانت على .دقيقة) ٥٠وقت النقع ( واخيرا )%٠١.٠( النسبة المئوية للجسيمات النانوية