metals Article
High Power Diode Laser (HPDL) for Fatigue Life Improvement of Steel: Numerical Modelling Stefano Guarino *
ID
and Gennaro Salvatore Ponticelli
Department of Engineering, University Niccolò Cusano, Via don Carlo Gnocchi 3, Rome 00166, Italy;
[email protected] * Correspondence:
[email protected]; Tel.: +39-3289816261 Received: 18 September 2017; Accepted: 18 October 2017; Published: 21 October 2017
Abstract: This paper deals with the improvement of fatigue life of AISI 1040 steel components by using a High Power Diode Laser (HPDL). First, the meaningfulness of each operational parameter was assessed by varying the experimental laser power and scan speed. After laser treatment, fatigue tests were performed to investigate the influence of laser processing parameters on the material resistance. The fatigue tests were carried out by using a rotating bending machine. Wöhler curves were obtained from the analysis of experimental results. Second, in the light of experimental findings, a 3D transient finite element method for a laser heat source, with Gaussian energy distribution, was developed to predict the temperature and the depth of the heat affected zone on the workpiece. The model allows us to understand the relationship between the laser treatment parameters and the fatigue enhancement of the components. HPDL was found to significantly increase the fatigue life of the irradiated workpieces, thus revealing its suitability for industrial applications. Keywords: steel; diode laser; hardening; fatigue life, finite element modelling
1. Introduction The improvement of mechanical strength and fatigue life of structural components is one of the most important objective to be achieved in order to satisfy the stringent requirements of today’s designers and producers [1–3]. Designing, monitoring, and providing innovative technological solutions aimed at improving the mechanical properties and in particular the fatigue life of steel components are therefore of fundamental importance [4,5]. During the last decades, many different approaches to improve the fatigue life of steels were proposed, i.e., heat and mechanical treatments, surface alloying, overlying coatings, etc. Among them, surface treatments on steel components have different applications in many technological domains. Generally, they are applied to obtain an improvement of hardness, wear resistance, and corrosion properties. These treatments permit steel components to meet the demand of high performance (load, pressure, wear, etc.) of the industrial world [6]. However, these processes, while having many advantages, are often expensive, time consuming, and do not allow a selective treatment of small portions of the component. In this respect, the use of lasers for the thermal surface treatment of steel components has appeared as an innovative solution since it offers selectivity, leaving areas not directly exposed to laser radiation unaltered, making process control very easy and facilitating manipulation [7–10]. A high power laser beam may be directed onto a surface using very precise multi-axis handling systems. A laser makes it possible to achieve extremely localized heating areas, remaining the bulk of the workpiece at the lower temperatures. The low temperature mass of the workpiece act as a heat sink during the cooling phase, allowing cooling rates of 103 –104 K/s suitable for the martensitic transition, resulting in increased wear and fatigue resistance of the component [11]. Moreover, when compared to other solutions, laser hardening causes little deformation of the part thanks to precise, controlled, and low heat input, thus
Metals 2017, 7, 447; doi:10.3390/met7100447
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virtually eliminating post-machining processes. In addition, laser sources can be applied to a wide range of materials [12–16]. All cast iron, medium-carbon steel, and tool steel are amenable to the laser hardening process [11], and even low carbon steels are amenable because of the rapid heating and cooling rates generated by the laser radiation [17]. On the other hand, the main disadvantage compared to conventional technologies is found with the effects of back tempering induced by multiple passes. In fact, a multi-pass hardening process is characterized form back-tempering phenomena. Every laser track re-heats the area previously heated, inducing a transformation of the martensite into tempered martensite characterized by lower hardness. Thus, the back tempering phenomena leads to a lack of uniformity of the surface mechanical properties [8,18]. A High Power Diode Laser (HPDL), different from other sources, is well suited to surface hardening. In fact, the HPDL beam profile ensures a uniform heating of the treated surface due to its characteristics: top-hat in the slow axis direction and Gaussian in the fast axis direction. The shape of the spot is typically rectangular or elliptical [19]. Finally, HPDLs have important advantages in terms of energy consumption, compactness, endurance, and running costs, making them suitable and appealing for many industrial applications [20]. To exploit the tremendous application potential of High Power Diode Lasers, research and development programs have been undertaken since 1994 [19,20]. Pashby et al. [21] reported the use of an HPDL for surface-hardening of a plain carbon and an alloy steel, investigating the relationships between laser power and processing speed. They achieved a constantly hardened depth and demonstrated the technical capability of diode lasers in surface hardening. Liu et al. [6] treated grey cast iron surface with diode laser to improve the hardness and wear resistance of the surface. They found that residual compressive stresses observed at the surface greatly enhance fatigue life and hardness. Fly et al. [22] treated low carbon steel by means of a low-power laser. Even in this case, an improvement in fatigue behavior was observed. In laser surface treatments, obtaining required hardness while minimizing thermal deformation is critical because structural components require high precision. Unfortunately, satisfying both the aforementioned requirements is a challenging task, and a good predictive model can significantly reduce time and costs in finding optimal process conditions. For this reason, extensive research has been carried out to either develop predictive models or uncover relationships between process parameters and process outcomes [23,24]. To have the possibility to carry out a full analysis of thermal treatment, it is necessary to have proper mathematical and numerical models that can provide information about instantaneous temperature fields, the change in time of fractions of particular phase proportions of the material, instantaneous stress distributions, and residual stresses. Currently, numerical methods are leading in the modelling of technological processes, allowing us to analyse complex shapes with any initial and boundary conditions. Moreover, numerical modelling is characterized by high elasticity with respect to numerical algorithm development and the possibility to consider variable thermo-physical parameters of the analysed problem [25–28]. In the present investigation, a High Power Diode Laser was used to improve the fatigue life of AISI 1040 steel workpieces. The interaction between laser source and steel surface was looked into by varying the laser operational parameters (i.e., laser power and scan speed). Laser treatment was performed by simultaneously rotating and translating the substrate under a stationary laser head to generate a helical scanning pattern. The effectiveness of the laser treatment was studied by rotating bending fatigue tests and microscopic analysis. In the light of experimental findings, a 3D transient finite element method for a laser heat source, with a Gaussian energy distribution, was developed to predict the temperature and the depth of the Heat Affected Zone (HAZ) on the AISI 1040 steel workpiece. The thermo-mechanical problem was solved sequentially in two phases. First, a transient thermal analysis was carried out in order to obtain the temperature distribution, which was used as input for the following static analysis. The experimental investigation demonstrated that HPDL surface treatment significantly increase the fatigue life of the irradiated workpieces, thus revealing its suitability for industrial applications. Furthermore, the simulation results turned out to be in good agreement with the experimental data.
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2. Experimental 2.1. Material and Methods A low carbon steel (AISI 1040) was chosen as the starting material due the suitability for thermal hardening treatments [17,29] and since it is commonly used in structural components as gears, shafts, axles, bolts, studs, couplings, and cold headed parts. The mechanical properties and chemical composition of the steel are reported in Table 1. The thermal properties are reported in Table 2. Starting from 2 m rods, 75 samples were cut with the geometry reported in Figure 1 (Φ 15 × 116 mm). The surface of the section, with diameter 6 mm, was machined with the same operational conditions, using a milling machine with medium finishing inserts. Surface hardening thermal treatments were performed using an HPDL (Rofin-Sinar model DL015, Plymouth, MI, USA) with a maximum peak power of 1.5 kW, wavelength of 940 nm and elliptical spot of 0.6 mm along the minor axis and 1.9 mm along the major axis. During the laser thermal treatments, the samples were held on a CNC turning device (DENFORD, Brighouse, West Yorkshire, UK) and processed by rotating them under the laser source as reported in Figure 2. For protection and insulation purposes, an inert gas flow of Argon was directed to the surface of the sample. Figure 2 reports a schematization of the system used. Table 1. Mechanical properties and chemical composition of AISI 1040. Property Rm (Mpa) E (GPa) ν HRC
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Temperature (°C) 0–100 Temperature (◦ C) 0–100 200 200 300 300 400 400 500 500 600 600 700
700
Value
Composition (wt %)
Value
670 C 200 Mn 0.3 Si Table13 2. Thermal propertiesPof AISI and S 1040.
Heat capacity (J/kgK)
0.37–0.44 0.50–0.80 0.15–0.40 ≤ 0.035
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Thermal Conductivity (W/mK)
Table 2. Thermal properties of AISI 1040. Heat486 capacity (J/kgK)
515 569 586 649 708 770
486 515 569 586 649 708 770
Figure 1. 1. Specimen Specimen geometry. geometry. Figure
50.7 Conductivity (W/mK) Thermal 48.1 45.7 41.7 38.2 33.9 30.1
50.7 48.1 45.7 41.7 38.2 33.9 30.1
Figure 1. Specimen geometry.
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Figure2.2.High HighPower PowerDiode DiodeLaser Laser(HPDL) (HPDL)system. system. Figure
Surface lasertreatments treatments followed the experimental schedule Table 3. The Surface laser followed the experimental schedule reportedreported in Table 3.inThe experimental experimental factors investigated were laser power and scan speed (peripheral speed calculated as factors investigated were laser power and scan speed (peripheral speed calculated as the product the product of thespeed rotational speed andof thethe radius the small section). and of passes of the rotational and the radius smallofsection). Focus and Focus number of number passes were fixed were fixed respectively at 0 and 1. For each condition investigated (that is, 25), the rotation speed and respectively at 0 and 1. For each condition investigated (that is, 25), the rotation speed and the beam the beam feed were properly chosen to ensure no overlap of the laser treatment. All the tests were feed were properly chosen to ensure no overlap of the laser treatment. All the tests were replicated replicated times (75 experimental After that, the area was characterized in terms three timesthree (75 experimental tests). Aftertests). that, the area treated wastreated characterized in terms of variations of variations in the extent of the hardened area (i.e., (Heat Affected Zone) HAZ). in the extent of the hardened area (i.e., (Heat Affected Zone) HAZ). Table Table3. 3.Experimental Experimentalfactors factors
Factors Laser power (W) Laser power (W) 100 Scan speed12(mm/s) Scan speed (mm/s) Factors
100 150 12 14
150 14
Values Values 200 250 200 16 18 16
300 250 20 18
300 20
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A four-point rotating bendingmachine machinewas was used used to to carry as as shown in in A four-point rotating bending carry out outthe thefatigue fatiguetests, tests, shown Figure 3. The samples were loaded with alternate cycles of tensile and compressive stresses as they Figure 3. The samples were loaded with alternate cycles of tensile and compressive stresses as were simultaneously bent and rotated. Loads from 10 to 16 kg were applied during the tests, they were simultaneously bent and rotated. Loads from 10 to 16 kg were applied during the tests, corresponding to an alternating stress (σMAX) in the range of approximately 320 to 460 MPa.
corresponding to an alternating stress (σMAX ) in the range of approximately 320 to 460 MPa.
Figure 3. Four-point rotating bending machine. Figure 3. Four-point rotating bending machine.
2.3. Numerical Model A thermo-mechanical numerical simulation was performed to describe the hardening process on the fatigue specimens. ANSYS code (ANSYS, Inc., version 17.2, Canonsburg, PA, USA) was used for the numerical model definition. The simulation first step was the thermal analysis that was carried out by using SOLID70 thermal elements. In the second step of the simulation, starting from the
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Figure 3. Four-point rotating bending machine.
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2.3. Numerical Model 2.3. Numerical Model
A thermo-mechanical numerical simulation was performed to describe the hardening process A thermo-mechanical numerical to describe the hardening processwas on used on the fatigue specimens. ANSYS codesimulation (ANSYS,was Inc.,performed version 17.2, Canonsburg, PA, USA) the fatigue specimens. ANSYS code (ANSYS, Inc., version 17.2, Canonsburg, PA, USA) was used for for the numerical model definition. The simulation first step was the thermal analysis that was carried the numerical model definition. The simulation first step was the thermal analysis that was carried out out by using SOLID70 thermal elements. In the second step of the simulation, starting from the by using SOLID70 thermal elements. In the second step of the simulation, starting from the thermal thermal solution, the thermal elements were converted into SOLID185 structural elements. At the solution, the thermal elements were converted into SOLID185 structural elements. At the end of end of simulation, radial displacement, and stress of specimen were evaluated, thethe simulation, the the radial displacement, strainstrain and stress of specimen were evaluated, in order in to order to have the specimen[30]. [30].An An axially symmetric object (standard have theprofile profileof ofthe the deformed deformed specimen axially symmetric object (standard tensiletensile test test specimen), 15 mm in outer diameter, innerdiameter, diameter, and in length, was subjected specimen), 15 mm in outer diameter,66mm mm in inner and 116116 mmmm in length, was subjected the simulation as reportedininFigure Figure 4, 4, where where the in both thermal and mechanical to thetosimulation as reported themeshes meshesused used in both thermal and mechanical calculations are presented. As shown in Figure 4, a finer mapped mesh was used in the area subjected calculations are presented. As shown in Figure 4, a finer mapped mesh was used in the area subjected to higher temperatures being directly located below the incident laser heat flux. This approach permits to higher temperatures being directly located below the incident laser heat flux. This approach to reduce modelling and solution times. permits to reduce modelling and solution times.
(a)
(b)
Figure 4. element mesh used in thermo-mechanical analysis: (a) general view; Figure 4. Finite Finite element mesh used in thermo-mechanical analysis: (a) general view; (b) local (b) ocal magnification. magnification.
The laser heating was modelled as thermal load by using a heat flux over an approximated elliptical spot of 3.8 × 1.2 mm2 . The laser beam power of 200 W was obtained by imposing a flux density of about 43.86 W/mm2 . The moving laser beam has a Gaussian distribution of heat flux. The model contains overall about 18,000 nodes and 36,000 elements. The starting environmental temperature was 20 ◦ C. The material properties used in the Finite Element Method (FEM) model are reported in Tables 1 and 2. The numerical model was calibrated using the following experimental scenario: laser power 200 W and scan speed 16 mm/s. In this experimental condition, thermocouples were used to obtain the experimental temperature profiles over time in three different tests. All the experimental thermal trends were compared with the numerical response of the model, as shown in Figure 5. The convective coefficients were chosen to have the best fitting between the experimental and numerical temperature profiles.
W and scan speed 16 mm/s. In this experimental condition, thermocouples were used to obtain the experimental temperature profiles over time in three different tests. All the experimental thermal trends were compared with the numerical response of the model, as shown in Figure 5. The convective coefficients were chosen to have the best fitting between the experimental and numerical Metals 2017, 7, 447 profiles. 6 of 12 temperature
Figure 5. Model calibration curve. Laser power = 200= W ScanScan speed = 16=mm/s. Figure 5. Model calibration curve. Laser power 200and W and speed 16 mm/s.
3. Results Discussion 3. Results andand Discussion Results show among the laser power values examined (see Table the treatments Results show thatthat among the laser power values examined (see Table 3), the3), treatments at 200 at W200 W highlight the best performance. These process conditions lead to a change in substrate properties highlight the best performance. These process conditions lead to a change in substrate properties without melting phenomena, with speed in the range 1620tomm/s. 20 mm/s. contrary, without melting phenomena, with scanscan speed in the range 16 to OnOn thethe contrary, the the treatment conditions at lower laser power (100–150 to significant changes in the treatment conditions at lower laser power (100–150 W) W) diddid notnot leadlead to significant changes in the morphology of the analysed substrates. In particular, any grain structure modification was observed. morphology of the analysed substrates. In particular, any grain structure modification was observed. Increasing power 300 independentlyfrom fromthe thescanning scanningspeed, speed, surface surface melting of Increasing thethe power to to 250250 oror 300 W,W, independently of the These results resultsare areiningood goodagreement agreementwith with literature results the specimen specimen was observed. These literature results [31][31] andand are are supported by the results reported in Figure It reports cycles of the specimen laser supported by the results reported in Figure 6. It6.reports life life cycles of the steelsteel specimen vs. vs. the the laser speed treatment obtained fixing laser power at the value of 200 W. The laser speed scanscan speed treatment obtained fixing the the laser power at the value of 200 W. The laser scanscan speed waswas found to be an influential factor in the process. Increasing the laser scan speed, the life of the specimen found to be an influential factor in the process. Increasing the laser scan speed, the life of the specimen increases. amount of thermal energy steel absorb during its treatment decreases, increases. TheThe amount of thermal energy the the steel cancan absorb during its treatment decreases, andand the the process reaches the condition in which it is possible have a martensitic transaction. The curves process reaches the condition in which it is possible to haveto a martensitic transaction. The curves trend trend indicates is a significant of the in the specimen treated with the indicates that therethat is a there significant increasingincreasing of the fatigue lifefatigue in the life specimen treated with the diode diode laser. More importantly, thethe nose of thecurve Wöhler for the laser-treated substrates is reached laser. More importantly, the nose of Wöhler forcurve the laser-treated substrates is reached at a at a number of that cycles is almost twiceofthat the untreated substrates (NT label in Figure 6). These number of cycles is that almost twice that theof untreated substrates (NT label in Figure 6). These results confirmed in literature in the study made from Guarino al. [18] in good results are are alsoalso confirmed in literature in the study made from Guarino et al.et[18] andand are are alsoalso in good agreement reported inpertinent the pertinent literature The increment the fatigue agreement withwith datadata reported in the literature [6,19].[6,19]. The increment of theof fatigue life canlife becan be attributed to the formation of a superficial annealed martensitic structure due to thermal attributed to the formation of a superficial annealed martensitic structure due to thermal phenomena phenomena induced by the laser treatment. The scan causes a furtherwhich heat treatment induced by the laser treatment. The subsequent lasersubsequent scan causeslaser a further heat treatment leads leads to of a slight annealing the steelphenomenon) (i.e., back tempering phenomenon) to awhich slight annealing the steel (i.e., backof tempering [29,32]. This phenomenon[29,32]. is clearlyThis phenomenon is 7, clearly reported Figure 7, which shows cross section of the steel heatreported in Figure which shows aincross section of the steela specimen heat-treated atspecimen 200 W and 20 mm/s in laser power and scan speed, respectively. In the latter figure, it is possible to observe that the martensitic transition reaches a thickness of about 180 µm. Laser treatments were carried out in order to maintain a constant laser scan speed. Due to the varying section of the sample, its rotating speed was accordingly changed when moving from the largest section zone of the substrate to the smallest one. It is worth to note that all the parameters were chosen to avoid or at least limit the overlapping phenomenon. As shown in Figure 8, each laser treatment started at point A, where the diameter of the specimen is the largest, and continued along the surface of the substrate passing to point B, varying the laser scan speed as mentioned before because of the decreasing of the diameter. Between the points B and C, the diameter is constant, as it is the laser scan speed. Finally, passing from C to point D, the diameter increases, and the laser scan speed is adjusted accordingly. Table 4 reports the interaction time between the laser beam and the specimen at
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different scan speed obtained along the constant section (i.e., from B to C). In particular, the lower the treated treatedatat200 200WWand and2020mm/s mm/sininlaser laserpower powerand andscan scanspeed, speed,respectively. respectively.InInthe thelatter latterfigure, figure,it itisis scan speed the higher the interaction time. It must be noticed that an excessive treatment time lead to possible possibletotoobserve observethat thatthe themartensitic martensitictransition transitionreaches reachesa athickness thicknessofofabout about180 180µm. µm. the back-tempering phenomenon while a too-short treatment time does not guarantee sufficient heat input required for the martensitic transition.
cycles vs.vs. laser scan (Laser power = =200 NT totothe Figure of cycles vs. laser scan speed (Laser power =W). 200 W). NT refers to the Figure6. 6.Number Numberofof cycles laser scanspeed speed (Laser power 200W). NTrefers refers theuntreated untreated samples. untreated samples. samples.
7. 7. laser hardened cross-section: Figure 7. Micrography ofof aa laser hardened cross-section: transition from: (a)(a) martensitic structure toto Figure Micrography a laser hardened cross-section: transition from: martensitic structure (b)(b) ferrite and perlite structure (Laser power 200 WW and Scan speed mm/s). (b) ferrite and perlite structure (Laser power == 200 W and Scan speed == 20 mm/s). ferrite and perlite structure (Laser power = 200 and Scan speed = 20 mm/s).
Laser Lasertreatments treatmentswere werecarried carriedout outininorder ordertotomaintain maintaina aconstant constantlaser laserscan scanspeed. speed.Due Duetotothe the varying varyingsection sectionofofthe thesample, sample,itsitsrotating rotatingspeed speedwas wasaccordingly accordinglychanged changedwhen whenmoving movingfrom fromthe the largest largestsection sectionzone zoneofofthe thesubstrate substratetotothe thesmallest smallestone. one.It Itisisworth worthtotonote notethat thatallallthe theparameters parameters were werechosen chosentotoavoid avoidororatatleast leastlimit limitthe theoverlapping overlappingphenomenon. phenomenon.AsAsshown shownininFigure Figure8,8,each eachlaser laser treatment started at point A, where the diameter of the specimen is the largest, and continued along treatment started at point A, where the diameter of the specimen is the largest, and continued along the thesurface surfaceofofthe thesubstrate substratepassing passingtotopoint pointB,B,varying varyingthe thelaser laserscan scanspeed speedasasmentioned mentionedbefore before because becauseofofthe thedecreasing decreasingofofthe thediameter. diameter.Between Betweenthe thepoints pointsB Band andC,C,the thediameter diameterisisconstant, constant,asasit it
Factors Values Table 4. speed Interaction time and fatigue 12 test results. untreated20 sample. Laser scan (mm/s) NT 14 NT refers 16 to the18 Interaction time (s) 0 15.71 13.46 11.78 9.42 Factors Values 10.47 1/2 0 3.96 3.66 3.43 3.23 3.06 √Interaction time (s ) Metals 2017, Laser 7, 447 scan speed (mm/s) 8 of 12 NT 12 14 16 18 20 Number of cycles 69,500 78,000 87,000 104,000 118,000 137,500
Interaction time (s) √Interaction time (s1/2) Number of cycles
0 0 69,500
15.71 3.96 78,000
13.46 3.66 87,000
11.78 3.43 104,000
10.47 3.23 118,000
9.42 3.06 137,500
Figure 8. CDCD areare characterized by aby varying section, while while BC hasBC a constant section. 8. Laser Laserpath: path:AB ABand and characterized a varying section, has a constant section. Table 4. Interaction time and fatigue test results. NT refers to the untreated sample.
Figure 9 shows the fatigue tests results in terms of number of cycles vs. the square root of laser Figure time 8. Factors Laser AB and CD characterized aValues varying section, while BC has a constant interaction withpath: the substrate. Theare latter term, whichby is suggested to be proportional to the laser section. power, as scan reported literature [12,32], allows of the Laser speedin (mm/s) NT 12 a better14understanding 16 18 dependence 20 of the Interaction (s)power itself. 0 As expected, 15.71 the number 13.46 11.78 decreases 10.47 as the laser 9.42 power fatigue√life from thetime laser of cycles 1/2 ) 0 3.66 3.43 3.23 3.06 Interaction time Figure 9 shows fatigue results in terms of number of cycles vs. the square increases (Figure 9). the It(s has beentests seen, from3.96 the experimental model regression, that there root is a of laser Number of cycles 69,500 78,000 87,000 104,000 118,000 137,500 dependencetime of fatigue life substrate. endurance The fromlatter the treatment time is according to the following regression interaction with the term, which suggested to be proportional to the laser model: power, as reported in literature [12,32], allows a better understanding of the dependence of the Figure 9 shows fatigue tests results in terms ofthe number of cycles vs. the square root of laser fatigue life from the the laser power itself. expected, (1)laser power =As −6.1 ∙ 10 √ + 2.5number ∙ 10 , of cycles decreases as the interaction time with the substrate. The latter term, which is suggested to be proportional to the laser increases (Figure 9). It has been seen, from the experimental model regression, that there is a where CN is the cycle number and t is allows the treatment The R2 is 0.95. power, as reported in literature [12,32], a bettertime. understanding of the dependence of the fatigue dependence of fatigue life endurance from the treatment time according to the following regression life from the laser power itself. As expected, the number of cycles decreases as the laser power increases model: (Figure 9). It has been seen, from the experimental model regression, that there is a dependence of fatigue life endurance from the treatment time according (1) = −6.1 · 10 √ to+the 2.5following · 10 , regression model:
√
5 where CN is the cycle number and The CN t=is−the 6.1 treatment × 104 t + time. 2.5 × 10 , R2 is 0.95.
(1)
where CN is the cycle number and t is the treatment time. The R2 is 0.95.
Figure 9. Number of cycles vs. laser interaction time (Scan speed = 20 mm/s).
3.1. Numerical Simulation Results
Figure9.9.Number Number cycles interaction time (Scan speed = 20 mm/s). Figure of of cycles vs. vs. laserlaser interaction time (Scan speed = 20 mm/s).
3.1. Numerical Simulation Results Figure 10 shows the temperature over the time for three different points (A, B, C) in a small section of the specimen during the laser treatment process. The peak temperatures were observed in proximity of the heat source position (point A). A high temperature gradient can be observed during the heating step, which is followed by the cooling phenomenon after the maximum temperature is reached.
Figure 10 shows the temperature over the time for three different points (A, B, C) in a small Figure 10 shows the temperature over the time for three different points (A, B, C) in a small section of the specimen during the laser treatment process. The peak temperatures were observed in section of the specimen during the laser treatment process. The peak temperatures were observed in proximity of the heat source position (point A). A high temperature gradient can be observed during proximity of the heat source position (point A). A high temperature gradient can be observed during the heating step, which is followed by the cooling phenomenon after the maximum temperature is the heating step, which is followed by the cooling phenomenon after the maximum temperature is reached. Metals 2017, 7, 447 9 of 12 reached.
Figure 10. Calculated temperatures temperatures for Figure 10. Calculated for nodes nodes A, A, B, B, and and C C over over time. time. Figure 10. Calculated temperatures for nodes A, B, and C over time.
Figure 11 shows the temperature map evolution during the hardening process simulation at two Figure 11 shows the temperature map evolution during the hardening process simulation at two s. The The laser laser scan scan speed speed was was set setat at20 20mm/s. mm/s. The maximum maximum temperature different times: 1.5 and 16 s. different times: 1.5 and 16 s. The laser scan speed was set at 20 mm/s. The maximum temperature reached is about 850 ◦°C, C, lower than the melting point of the material (1515 ◦°C). C). This scenario clearly reached is about 850 °C, lower than the melting point of the material (1515 °C). This scenario clearly indicates that thatallallexamined examined points are outside the fusion “window” and in thermal the right thermal indicates points are outside the fusion “window” and in the right conditions indicates that all examined points are outside the fusion “window” and in the right thermal conditions for the transition. hardening transition. for the hardening conditions for the hardening transition.
Figure 11. 11. Temperature distribution during during the the hardening hardening process process of of AISI AISI 1040 1040 steel steel specimen specimen at at two two Figure Temperature distribution Figure 11. Temperature distribution during the hardening process of AISI 1040 steel specimen at two different times: (a) t = 1.5 s; (b) t = 16 s. different times: (a) t = 1.5 s; (b) t = 16 s. different times: (a) t = 1.5 s; (b) t = 16 s.
As showed in Figure 12, the FEM model allows identifying the substrate thickness of the As showed 12,12, the the FEMFEM model allowsallows identifying the substrate thicknessthickness of the workpiece As showedininFigure Figure model identifying the substrate of the workpiece with a temperature profile of greater 600 °C. This area corresponds to the HAZ zone ◦ C.than with a temperature profile of greater than 600 This area corresponds to the HAZ zone where there workpiece with a temperature profile of greater than 600 °C. This area corresponds to the HAZ zone where there are the thermal conditions for the martensitic transition. Figure 12 shows a good are the there thermal for the martensitic Figuretransition. 12 shows aFigure good agreement where areconditions the thermal conditions for transition. the martensitic 12 shows between a good agreement between the simulation (Figure 12a) and experimental results (Figure 12b) being, in both the simulation (Figure and experimental (Figure 12b) results being, in both cases, the hardened agreement between the12a) simulation (Figure 12a)results and experimental (Figure 12b) being, in both cases, the hardened thickness of about 180 µm. In particular, the simulation predicts a slightly thickness about 180 µm. In particular, theµm. simulation predictsthe a slightly shallower depth for all cases, the of hardened thickness of about 180 In particular, simulation predicts a slightly shallower depth for all the scan speed investigated. It must be noticed that the fitting between the the scan speed It must be investigated. noticed that the fittingbebetween and the the shallower depthinvestigated. for all the scan speed It must noticedthe thatnumerical the fittingmodel between numerical model and the experimental data is characterized by a mean absolute error of ~7%. The experimental data is characterized by a mean absolute error of ~7%. The matching between the FEM numerical model and the experimental data is characterized by a mean absolute error of ~7%. The model and the experimental data can therefore be considered very good, even if it is compared with data available in the literature [11,24,33].
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matching the FEM model and the experimental data can therefore be considered very 10 good, Metals 2017, between 7, 447 of 12 even if it is compared with data available in the literature [11,24,33].
Figure Zone (HAZ) in (a) and (b) experimental model (Laser = Figure 12. 12. Heat HeatAffected Affected Zone (HAZ) innumerical (a) numerical and (b) experimental modelpower (Laser 200 W and Scan speed = 20 mm/s). power = 200 W and Scan speed = 20 mm/s).
The reliability of the developed FEM model is also confirmed by considering the data that the The reliability of the developed FEM model is also confirmed by considering the data that the simulation can predict in terms of max stress vs. cycle number. In the experimental test, sample simulation can predict in terms of max stress vs. cycle number. In the experimental test, sample rupture is taken when there is a strong reduction in the stress level compared to the stabilized cycles. rupture is taken when there is a strong reduction in the stress level compared to the stabilized cycles. In In numerical simulation, this method is not suitable for predicting sample failure. However, the numerical simulation, this method is not suitable for predicting sample failure. However, the model is model is able to make a good prediction of the maximum stress vs number of cycles providing a able to make a good prediction of the maximum stress vs number of cycles providing a useful support useful support for the experimental investigation. for the experimental investigation. 4. 4. Conclusions Conclusions A HighPower PowerDiode DiodeLaser Laser source adopted to investigate its capability to increase the A High source waswas adopted to investigate its capability to increase the fatigue fatigue life1040 of AISI steelbysamples by the thermal-surface-hardening process. of the life of AISI steel1040 samples the thermal-surface-hardening process. Analysis of theAnalysis microstructure microstructure of the specimens revealed two main different areas: (i) a topmost area characterized of the specimens revealed two main different areas: (i) a topmost area characterized by a homogenous by a homogenous distribution of the annealed martensite (ii) an unaltered areaperlite made distribution of the annealed martensite and (ii) an unalteredand underling area madeunderling of ferrite and of ferrite and perlite structure. From the experimental results, the following conclusions can be structure. From the experimental results, the following conclusions can be drawn: drawn: Themost mostsuitable suitablethermal thermalconditions conditions (i.e., (i.e., change change in in structure structure without melting phenomena) are •• The reachedwith withaasingle singlelaser laserscan scan by by using using aa laser laser power power of of 200 W and a scan speed of 20 reached 20 mm/s. mm/s. Lowerlaser laserpower powerhas hasno noeffect, effect, higher higher laser laser power power causes causes the surface melting. In both cases, the Lower resultisisindependent independentof ofthe thescan scanspeed speedadopted. adopted. result •• The Thelaser laserthermal thermalsurface surfacetreatment treatmentincreases increases the the fatigue fatigue life life of of treated treated material material with respect to the theuntreated untreatedmaterial. material. •• The Zone was consistently found to depend on the fluency. An Theextent extentofofthe theHeat HeatAffected Affected Zone was consistently found to depend on laser the laser fluency. excessive treatment time or a too-high laser power inhibit the thermal conditions required for the An excessive treatment time or a too-high laser power inhibit the thermal conditions required for martensitic transition. This This is due the heat heat inputinput supplied to the the martensitic transition. is to due toexcessive the excessive supplied tosample. the sample. Finally, in the light of experimental findings, a Finite Element Method model was developed Finally, inwith the light of experimental findings, Finite Method model wassimulation. developed The and and validated the aim to have a suitable tool afor laserElement surface hardening process validated with the aim to have suitable tool for laser surface hardening process simulation. The comparison of experimental andanumerical results revealed a good correlation for both the extent of comparison of experimental and numerical results revealed a good correlation for both the extent of the Heat Affected Zone and fatigue life with an error of ~7% and ~4%, respectively. The experimental the Heat Affected Zone and fatigue life with an error of ~7% and ~4%, respectively. The experimental
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results show the great potential of High Power Diode Laser for the surface hardening of steel substrates, and the simulations reveal the capability of the Finite Element Method solutions to be very helpful in predicting, controlling, and managing the laser surface hardening processes. Acknowledgments: The authors gratefully acknowledge the CIRTIBS Research Centre of the University of Naples Federico II and the Department of Enterprise Engineering of University of Rome Tor Vergata for providing the equipment, the materials, and the technical support necessary to develop this research work. Author Contributions: Stefano Guarino conceived and designed the experiments; Stefano Guarino and Gennaro Salvatore Ponticelli performed the experiments, analyzed the data and wrote the paper. Both authors have read and approved the final manuscript. Conflicts of Interest: The authors declare no conflict of interest.
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