Process Efficiency

As defined by Niles and Jackson (1975) the process efficiency is expressed as the ratio of the total energy delivered to the workpiece (per unit of length) – heat input – to the energy input generated by the power source – arc energy. Process efficiency influences the distribution of temperature and cooling rate, and therefore the heat flow models discussed above should consider the application of this factor. In this perspective, the quantification of the process efficiency is a fundamental measurement to achieve precise models for the distribution of temperature, where heat input is applied.

Different analytical methods and experimental techniques have been found in the literature to quantify process efficiency, but a wide spread of results is observed.

3.1.3.1. Analytical Methods

The theoretical and numerical models of heat flow have often been developed considering estimations of the heat losses during welding. The process efficiency was estimated from the modelling development using thermal cycle measurements.

An analytical development of the model of Rosenthal was performed by Niles and Jackson (1975) to predict the process efficiency in GTAW using thermal cycle measurements. The equation obtained by those authors (Niles and Jackson 1975) was based on conduction heat transfer and constant thermal properties were considered:

𝑇−𝑇₀ temperature and Hi is the actual heat input, i.e., the heat absorbed by the workpiece during the welding. Results obtained for process efficiency of GTAW were in the range of 31% to 64%. The authors suggested that the wide range of results was associated with the welding conditions applied.

Giedt et al. (1989) analysed the process efficiency based on temperature field measurements, obtaining results in the range of 50 to 62%. They pointed out that the solution presented by Niles and Jackson (1975) did not include the convection associated with the fluid flow, as described by by Heiple and Roper (1982) or the effect of varying thermal conductivity with temperature. They also reported that other assumptions made by Niles and Jackson (1975) could explain the low values obtained for the process efficiency.

Dutta et al. (1994) used a combined experimental/ computational method to estimate process efficiencies of GTAW under quasi-steady conditions for low alloy steel. Digitized free surface images using a pulsed laser vision system were applied to obtain instantaneous measurements of the weld pool length on both sides of the electrode. Width and depth optical measurements made possible the development of three-dimensional model which was able to quantify process efficiency. The results of process efficiency determined using

153 that experimental/modelling approach was in the range of 62% to 85%. The authors attributed the wide variation of the results to the changes in arc current, voltage and welding speed. They also considered other factors which were fixed but may affect process efficiency, such as the arc length, electrode tip angle, shielding gas composition, flow rate and parent material.

It is clear that “process efficiency” has often been used as an adjustable parameter in order to match predictions from theoretical models with experimental measurements. Hence, there will always be significant doubt associated with the values of process efficiency determined in this way, since many other factors associated with model limitations and material properties can affect the calculated process efficiency.

3.1.3.2. Experimental Methods

A water-filled calorimeter method was used by Essers and Walter (1981) to measure the amount of heat transferred to the workpiece for GMAW. Metal strip specimens were placed in the calorimeter, almost totally immersed in water with only the upper surface just above the water level, and the water temperature variations were registered. A constant distribution of water temperature was ensured through the use of a rotating blade. Heat losses from the surface of the metal strip occurred, resulting in an error estimated at 5%.

This method was applied to quantify the process efficiency in plasma-GMAW and GMAW.

Essers and Walter (1981) measured a process efficiency of 23% for non-transferred plasma (no current through the workpiece) without wire addition, 54% for transferred plasma without wire addition, 65% for plasma-GMA welding, and 71% for GMAW. They considered that although the cathode (workpiece) was the same in all cases, the anode varied between the tests performed, resulting in the differences between the results obtained. GMAW had only one anode (filler metal), while plasma-GMA had two anodes (the filler metal and non-consumable plasma).

A water calorimeter was also used by Quintino (1986) to measure the process efficiency for GMAW-P. The calorimeter tests were based on water temperature variation, before and immediately after welding, using bead on plate samples with 15mm thickness. She compared the variation of process efficiency using different welding conditions, such as mean current (100, 150 and 200A), filler wire diameter of 1.0, 1.2 and 1.6mm and two different gas mixtures (5%CO2 95%Ar and 1.5%CO2 85%He 13.5%Ar). CTWD of 20mm was kept constant in all tests performed. With those tests Quintino (1986) found that mean current does not affect significantly welding process efficiency. However, the variation of filler wire, using shielding gas 5%CO2 95%Ar, might have some influence with a process efficiency of 66% for 1.2mm, against 59% and 60% for 1.0mm and 1.6mm diameter wire, respectively. Trials using 1.2mm filler wire and 1.5%CO2 85%He 13.5%Ar gas mixture confirm the results for the other mixture, with process efficiency average values of 67%. The

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results obtained by Quintino (1986) are in agreement with the previous results obtained by Essers and Walter (1981) for GMAW.

Analytical/ numerical estimations obtained by Christensen et al. (1965) (21-48%) and Niles and Jackson (1975) (35-65%) are much lower than the results obtained using a water cooler calorimeter. However, other water cooled anode measurements for GMAW are reported by Giedt et al. (1989) to have significantly higher process efficiency, in the range of 80 – 90%

(Wilkinson and Milner 1960) (Tsai and Eagar 1984).

Lu and Kou (1989) used a water calorimeter to measure the process efficiency and heat input for GMAW of aluminium. The calorimeter consisted of an insulated stainless steel rectangular box. A water supply system was used by those authors to maintain a constant water flow rate. They ensured that no bubble formation due to water vaporization was achieved. Continuous water temperature measurements, using differential thermistors, were recorded and the heat absorbed was calculated using the specific heat of water (Figure 3.2).

a) b)

Figure 3.2 – Measurement of process efficiency in GTAW: a) Calorimeter; b) variation of water temperature as a function of time.

Process efficiency of 80% was measured, and contributions of 45% from arc radiation and convection, 23% from filler metal droplets and 12% associated to the cathode heating were estimated by the authors (Lu and Kou 1989). These results are significantly higher than the previous results obtained by Quintino (1986) and Essers and Walter (1981) for GMAW using steel. It was suggested that the material properties may justify the higher valued obtained for aluminium.

Bosworth (1991) measured the effective heat input in GMAW and GMAW-P, using a water calorimeter method. He analysed the variation of different welding conditions, such as the arc current, arc length, shielding gas mixtures in blends of argon-carbon dioxide. This author remarked for the first time that arc power calculations could have a significant effect on the results of process efficiency and suggested that the average of instantaneous power should the applied to calculate true power. An average of 85% for the process efficiency in GMAW, at wide range of burn-off rates, and 95% for short-circuiting transfer were obtained. In GMAW-P process efficiencies between 80% and 85% were observed, with the lower values obtained at high WFS. Bosworth (1991) considered that WFS has a major impact on process efficiency, and gas composition has a minor but still significant effect. It is noticed that the

155 results measured by this author are significantly higher when compared with earlier measurements obtained by other authors (Quintino 1986) (Essers and Walter 1981) (Lu and Kou 1989). The differences may be due to the different measurement techniques used or the method used to calculate arc power values.

A gradient layer type calorimeter was applied by Giedt et al. (1989) to measure the process efficiency. This method consists on the measurement of the temperature drop in a thin layer of the material due to the heat flow. The measurement is achieved using a thermocouple circuit placed on the inner and outer surfaces of the layer. A thermopile is formed by series of these circuits, multiplying the thermoelectric output of the system. That combination of thermopiles and gradient layers formed a heat-rate meter based on the Seebeck thermoelectric effect, and therefore it has been called a Seebeck Envelope Calorimeter (Figure 3.3.)

a) b)

Figure 3.3 – a) Schematic sketch of Seebeck calorimeter applied to measure process efficiency; b) operating principle of a gradient layer calorimeter.

These authors (Giedt, Tallerico and Fuerschbach 1989) reported that those measurements took up to 6 hours for the workpiece normalize the temperature with the water cooler.

Results of process efficiency for GTAW were in the range of 80%, even considering the variation of arc current, voltage and electrode diameter. The results of process efficiency reported did not include any correction to heat losses by radiation, convection and vaporization, but the authors estimated those to be smaller than 1%.

Fuerschbach and Knorovsky (1991) performed an intensive study using a Seebeck calorimeter on plasma arc welding and GTAW. The process efficiency results obtained by

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those authors were in the range of 50 to 75% for plasma arc welding and 80% for GTAW with continuous and pulsed current conditions. Those numbers were in agreement with previous results obtained by Giedt et al. (1989) for GTAW.

Using a Seebeck envelope calorimeter, Cantin and Francis (2005) investigated the process efficiency of GTAW in aluminium (Figure 3.4). They compared the process efficiency in GTAW using AC polarity and DC with electrode positive and negative polarities. Isolating materials were applied to the specimens in order to reduce losses occurring during the welding. They investigated the effects of the variation of shielding gas composition, arc length and arc current on the power and process efficiency obtained. The results obtained for DCEN polarity, where the majority of the heat is transferred by the electrons, varied between 76% and 89%; with the highest values obtained when helium was used as a shielding gas. These results show a significant effect of the shielding gas on the process efficiency measured, and are in agreement with a similar work developed by Zijp and Den (1990) and Hiraoka et al. (1998), as reported by Cantin and Francis (2005). Using AC polarity and DCEP polarity, the power and process efficiencies could be estimated based on weighted average of EN (electrode negative) fraction under identical weld conditions. For DCEP polarity, where the electrons are supplied by the workpiece, a much colder process occurs and temperature is too low for thermionic emission to occur. In this case a cathode voltage drop takes place at the cathode as reported by Cantin and Francis (2005).

Nonetheless, the process efficiency obtained is much lower with values in the range of 52 to 60%. They observed that the highest values are also associated with the highest amounts of helium. Process efficiency assessed for AC polarity varied in the range of 65 to 83%. The highest values were also obtained for the richest helium gas mixtures (75% and 100%). Arc length changes assessed in this study did not demonstrate a significant effect on the process efficiency.

a) b)

Figure 3.4 - a) aluminium specimens used in the experiments with the approximate location of thermocouples (marked by an “x”); b) schematic representation of the calorimeter.

Although water calorimeters have been extensively used in the past, they are time consuming with possible errors in the results obtained. Liquid nitrogen calorimetric tests were firstly introduced by Smartt et al. (1985) , as described by Kenney et al. (1998) and Dutta et al. (1994), who obtained process efficiencies between 71 and 84% for GMAW.

157 A liquid nitrogen calorimetric method was also used by Kenney at al. (1998) to analyse heat transfer in GMAW-P. They used a six litres stainless steel dewar and an electronic scale interfaced to a computer, where they measured the loss of weight associated with liquid nitrogen vaporization. Rapid transfer of welded specimens from the welding rig to the calorimeter was obtained. The results of process efficiency obtained were in the range of 69 to 82%, and with an average of 72%. They concluded that the process efficiency obtained for GMAW could not be directly related variations in pulse parameters, for either constant current or constant voltage. The technique used by those authors resulted in slightly higher values for the process efficiency compared with the tests performed using water calorimeter.

Joseph (2001) also used liquid nitrogen calorimetric tests to compare the process efficiency obtained with a wide variation of pulse parameters for GMAW-P, and compared different ways of calculating arc power. The average of the instantaneous arc power, average power (product of the average of arc current by average arc voltage), and the RMS power were considered in his study. The process efficiency obtained changed considerably using these different methods – 70.2% using instantaneous arc power calculations, 82.4% for the average power and 60.7% for RMS power.

More recently, Hsu and Soltis (2003)have undertaken an investigation on process efficiency using liquid nitrogen calorimetric tests, where STT, short-circuiting and pulsed GMAW and CV GMAW were compared. The results demonstrated that process efficiency is lower for CV spray and pulsed spray GMAW at 73%, while CV short-circuiting and STT presented higher results, respectively 85% and 86%.

Recently, Egerland (2009) have investigated the process efficiency on a narrow groove using CMT-P and GMAW-P. Although a limited number of tests have been undertaken and experimental errors were not estimated, there is an indication from this work that process efficiency is significantly higher, within approximately 10%, for applications using square groove geometry (process efficiency of 85%).

Among the work published on the analysis of process efficiency, considering both the experimental and analytical models, a wide spread of results has been observed. It is clear that material properties and welding process can play an important role on the values of process efficiency obtained. Calorimetric tests are always more reliable than calculations obtained based on assumptions and unsteady criteria defined by the analytical approaches.

Nonetheless, with the new significant developments in arc welding technology and the importance of the application of process efficiency parameter in modelling studies, a more reliable study is required to determine which welding parameters affect welding process efficiency, and how it changes with waveform design.

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