D. J. Varacalle, Jr. and D. P. Zeek
Idaho National Environmental and Engineering Laboratory (INEEL)
Idaho Falls, Idaho 83415

V. Zanchuck and E. Sampson
Tafa, Inc.
Concord, NH 03301

K. W. Couch and D. M. Benson
Protech Lab. Corp.
Cincinnati, OH 45241

G. S. Cox
ITI Anti-Corrosion, Inc.
Houston, TX 77036

Experimental studies of grit blasting, twin-wire electric arc (TWEA) spraying of zinc and aluminum coatings, and combustion spraying of polymer coatings were conducted to demonstrate suitability of the systems for anti-corrosion applications at the Idaho National Engineering and Environmental Laboratory (INEEL). Experiments were conducted using statistically designed experiments. The statistical design-of-experiment (SDE) approach for the thermal spray process is ideal because it displays the range of measured coating characteristics attainable, and it statistically delineates the impact of each process parameter on the measured coating characteristics across all combinations of the other parameters. Grit blasting was investigated to ensure a strong mechanical bond between the substrate and the thermal spray coatings by enhanced roughening of the substrate material. Coatings were characterized with bond strength and deposition efficiency tests, and optical metallography. Coating properties were quantified with respect to roughness, porosity, thickness, bond strength, and microstructure. Performance evaluation of the coatings was quantified by accelerated corrosion testing. Coating designs were verified by confirmation testing.

This work has selected technology and equipment to refurbish waste containers at the Radioactive Waste Management Complex (RWMC) to enable transport and storage of INEEL transuranic (TRU) waste drums to the Waste Isolation Pilot Plant (WIPP). Much of the TRU waste stored at the INEEL is in Department of Transportation (DOT) type A certified 55-gal steel drums. Degradation of many of these containers has raised concern regarding safe storage, handling, transportation, and disposal of the waste [1]. Refurbishment of these metal drums is to be without repackaging or overpacking the contents. The methodology evaluated surface preparation techniques such coatings as metals, polymers, paints, and sealants. The processes selected were required to be WIPP/WAC acceptable, including requirements determined from the WIPP performance assessment. Refurbishing the drums involves off-the-shelf technology. The specified coatings procedure will restore integrity to currently stored degraded 55-gal waste containers, eliminating need to overpack containers, and extending the storage life by providing an economical protective coating to inhibit corrosion. It will improve the appearance as well. Refurbishing WIPP-certifiable drums significantly saves costs compared to overpacking the drums.

Thermal spray [2] is a versatile group of processes used to apply metallic and nonmetallic coatings, combining particle melting, quenching, and consolidation in a single operation. Thermal spray coatings offer effective, long-term corrosion protection for iron and steel structures over a wide range of corrosion environments, and are viable to refurbish waste repositories and waste containers. Protection against corrosion will last for up to 20 years without maintenance and up to 40 years with minimal maintenance. The current method to address problems with container integrity at the INEEL is to overpack into larger containers. Approximately 10% of the accessible stored CH-TRU waste in 55-gal drums has been overpacked into 83-gal overpack drums (3,052 of 29,002 examined were overpacked as of March 10, 1997). The 83-gal drums cannot currently be characterized for transport and disposal at WIPP. Refurbishing is preferable to overpacking. The advantage of the proposed coating methodology is that it would restore and retain CH-TRU inventory in 55-gal drums, which meets the Settlement Agreement milestone. The Settlement Agreement between the State of Idaho, the DOE, and the U.S. Navy concerning removal of nuclear waste from the INEEL has produced an urgency to implement technology to expedite shipment. The agreement states that 3100 m^3, or 14,904 55-gal drum equivalents of TRU waste must be shipped from Idaho by December 31, 2002, and all INEEL TRU waste be shipped from Idaho by December 31, 2018.

The coating for the waste containers must be compatible with the waste container materials and to withstand the normal operating environment of the containers. Requirements include thermal (service temperature, thermal shock) and chemical (corrosion) conditions, which dictated choice of the materials for the coatings. The coatings for the containers must withstand a low-to high humidity air atmosphere for the application, and must maintain integrity against temperature cycling, from freezing to 38°C (100°F).

A substantial range of grit blasting parameters and their effect on the resultant substrate roughness were investigated. The investigation included grit type, pressure, working distance, and exposure time. The substrates were characterized for surface characteristics using image analysis. These attributes are correlated with the changes in operating parameters. Optimized process parameters are presented for the two machines used in the study as predicted by the SDE analysis.

The experimental study of the TWEA spraying of zinc, aluminum, and zinc/aluminum alloy coatings demonstrates suitability of the systems for site application. The process parameters that were varied include nozzle diameter, current, spray distance, and system pressure. Systematic design of experiments was used to display the range of processing conditions and their effect on the resultant coating. The coatings were characterized with bond strength and deposition efficiency tests, and optical metallography. Coating properties were quantified with respect to roughness, porosity, thickness, bond strength, and microstructure. Performance evaluation of the coatings was quantified with accelerated corrosion testing. Confirmation testing verified the coating designs.

Studies of the subsonic combustion (Flame) process were conducted to determine the quality and economics of polyester and urethane coatings for use as sealants for the metal coatings. Thermally sprayed polymer coatings are of interest to several industries for anticorrosion applications, including the chemical, automotive, and aircraft industries. Optimized coating designs are presented for the polyester and urethane powder systems. A substantial range of thermal processing conditions and their effect on the resultant polymer coatings is presented. The coatings were characterized by optical metallography, hardness testing, tensile testing, and compositional analysis. Characterization of the coatings yielded the thickness, bond strength, Knoop microhardness, roughness, deposition efficiency, and porosity. Confirmation testing verified the coating designs.

Thermal spray is a generic term for a versatile group of processes for applying metallic and nonmetallic coatings. These processes include flame (combustion), plasma, and electric arc. Coating materials include all types and combinations of ceramics, carbides, metals, composites, and plastics available in powder, wire, or rod form. These coatings can provide virtually any type of surface performance and functional application. The processes are particularly suitable for forming coatings for various industrial functions, including wear resistance, heat and oxidation resistance, diffusion barriers, atmospheric and aqueous corrosion resistance, electrical resistance and conductivity, dimensional restoration, abradables, abrasives, clearance control, electromagnetic interference shielding, and chemical corrosion resistance.

The grit blast process involves spraying of abrasive particles against the surfaces of parts or products to remove contaminants and condition the surfaces for subsequent finish operations. The coatings rely primarily on mechanical bonding to the substrate. Thus, it is critical that the substrate be properly prepared to ensure maximum coating bond strength.

In the TWEA process, two wires are brought together and an electric arc is struck between them. Typical dc voltages are between 20 and 35 volts with current ranging up to 350 amperes or more. Wire feedrate is governed by the system current. The arc developed between the two wires causes the wire tips to melt and superheat. An atomizing gas, typically air, is delivered to these two wires to strip off small droplets of molten metal. In this way, kinetic energy is transferred to the droplets. Typical air flow rates range from 850 to 1699 Lpm [30 to 60 standard cubic feet per minute (scfm)]. It is common to spray nitrogen or argon to reduce formation of oxides on the molten droplets. In general, any material that is electrically conductive and can be made into a wire can be sprayed with a TWEA device. The process is capable of attaining high bond strengths for even complex geometries. Figure 1 shows the Tafa Model 9000 TWEA arc spray gun used in this study.

Combustion spraying was the first thermal spray process developed to apply coatings [2]. The process uses combustible gases as a heat source to melt the coating materials, which are in powder, wire, or rod form. The commonly used combustion spray gases are oxygen, acetylene, propane, and hydrogen. The most common fuel for the Flame process is acetylene, since it can obtain the maximum flame temperature (3350°C) when burned with oxygen. The materials are introduced into and melted in the combustion gases, and the subsequent molten particles/droplets are accelerated to the substrate by the gas flow. Flame temperatures and characteristics depend on the stoichiometric combustion temperatures of the oxy-fuel mixtures. The process is temperature limited and generally used for materials with low melting points. The ratio or stoichiometry of fuel to oxygen is important in determining the final coating structure. Stoichiometric combustion for acetylene requires a 2.5:1 ratio of oxygen molecules to acetylene molecules (2C2H2 + 5O2 = 2H2O + 4CO2). This combustion ratio produces a neutral flame (each oxygen and acetylene molecule is consumed during combustion).

A natural sequence occurs in most experimental programs. In the early stages, classical screening experiments are conducted to identify potentially influential process parameters. In the middle stage, the experimenter knows which parameters influence the responses, but he or she requires a more quantitative understanding of the main effects, the possible interactions between the effects, and experimental error. Fractional-factorial and factorial designs are used in this stage. In the later stages, a thorough quantitative understanding of the effects of relatively few parameters is required and obtained by using optimization (i.e., response surface) strategies.

Effects analysis was first conducted for the coating responses. For each response, the factor coefficients were calculated using least squares estimates. Analysis of variance (ANOVA) analysis was conducted to determine the adequacy of the statistical models. Once a model was chosen, each response was analyzed using the following methodology: the model was analyzed for in-depth regression analysis, diagnostic evaluation of the robustness of the model was determined, response surface analysis was conducted, and coating attributes were then numerically optimized.

Statistical analysis used commercially available software (Design-Ease, Design-Expert) [3]. The program first fits linear (main effects only), quadratic (linear effects plus square of main effects, and two-factor interactions), and cubic polynomials (quadratic effects plus cube of main effects and cubed interactions such as A2B and ABC) to the data. The ANOVA calculations provided a sequential comparison of models, showing the statistical significance of adding additional model terms to those terms already in the model.

Analysis then determined the optimum parameters for the coating designs. The methodology involved numerical optimization to search for a combination of parameter levels that simultaneously satisfies the requirements placed on each of the responses. A desirability function reflects the most desirable combination of the coating attributes. The function simultaneously optimizes all the coating attributes using a scale from 0 to 1 (least to most desirable, respectively). The assumptions used for the numerical optimization involved subjective priority weighting.

The statistical methodology employed is significant because it finalizes coating design studies by optimizing the most important process or coating attributes and the process parameters affecting these attributes.

Five statistically designed experiments [4] were used to investigate the grit blasting process. The experiments were conducted using a Box statistical design of experiment (SDE) approach [5]. A substantial range of grit blasting parameters and their effect on the resultant substrate roughness were investigated. The investigation included grit type, pressure, working distance, and exposure time. The substrates were characterized for surface characteristics using image analysis. The attributes are correlated with the changes in operating parameters.

The major reason for grit blasting before thermal spray application is to ensure a strong mechanical bond is achieved between the substrate and the coating by the enhanced roughening of the substrate. The process involves spraying of abrasive particles against the surfaces of parts or products to remove contaminants and condition the surfaces for subsequent finish operations. The capability of the processes to achieve maximum bond strength is crucial to the success of any particular application. Thermal spray coatings rely primarily on mechanical bonding to the substrate. Thus, it is critical that the substrate be properly prepared. Surface cleanliness and roughness are the most critical factors.

Two devices were used for the abrasive blasting experiments: an Econoline, RA 36-1 Blast Cabinet [6], and a Clemco pressurized-pot blaster [7]. The Econoline cabinet is rectangular and is a self-contained, recycling, sealed glove box design. It is capable of blasting small pieces. The blasting media is drawn into the gun through a siphon tube connected to the base of the gun's pistol grip. A pressure regulator on the cabinet exterior allows the operator to regulate air supply pressure. An external dust collector sweeps and filters the air in the cabinet to improve visibility during blasting.

The Clemco blast machine is a much larger device, capable of blasting very large pieces or structures. The device is a nonrecycling, pressurized pot design and consists of a large, upright, cylindrical pressure-tight hopper with a funnel base. Two lines connect to the hopper. The air pressure supply line connects to the side of the hopper, pressurizes the hopper, and directs air flow down to the mixing connection. The other line connects to the bottom of the hopper and meters the abrasive media into the air stream. The flow out of the mixing connection is directed through a blasting hose. The blasting media is accelerated and directed to the working surface of the piece through a venturi nozzle.

The parameters optimized in the grit blast studies included working distance, exposure time, blast media, and pressure. Cross-sections of the surfaces of the target samples grit blasted with the various parameters were prepared for metallographic examination. The surfaces produced by grit blasting with the Econoline system appeared to be relatively free from embedded grit or surface scale particles, whereas foreign particles were frequently seen embedded in the surfaces produced with the Clemco system. The attributes evaluated were average roughness, maximum peak-to-peak height, normalized line length, and the surface area enhancement factor (SAEF).

The effects analysis indicates the Clemco equipment (used in experiment sets WC and WS) roughens the substrates more than the Econoline equipment (experiment sets IA, IC, and IS), with larger amplitudes and slightly larger normalized line lengths. Three types of abrasive blast media were used for the experiments. These included 35-mesh copper slag, 35-mesh silica sand, and 60-mesh alumina grit. Copper slag grit resulted in more surface modification than the other grits for the Econoline machine, whereas there was little difference between the silica and copper grits used in the Clemco machine. SAEFs for the grit blasted surfaces produced by the Clemco system range from 1.1 to 4.3, whereas the SAFEs produced by the Econoline system ranged from 1.3 to 3.3, indicating enhanced surface finish with the Clemco machine.

Relative to the statistical analysis, there was a significant variance for the surface attributes from the Econoline machine for the three grit materials used. Interaction effects overwhelm the main effects for all four surface attributes for the copper slag study. Working distance and pressure had little to no effect on the surface conditions for the alumina study, whereas longer exposure time significantly increased all four surface attributes. In the silica study, the surface characteristics were relatively insensitive to exposure time and working distance for the roughness and amplitude, whereas pressure was a significant contributor to modifying all four surface characteristics The silica study for the Clemco machine indicates significant interaction effects. All four surface attributes indicate the optimum process parameters are at the lower level of working distance, exposure time, and pressure. This correlates with the characterization analysis for the study. The copper slag study indicates strong dependence on working distance with a secondary influence from the system pressure. All four surface attributes indicate the optimum process parameters are at the lower level for working distance and exposure time, and the maximum pressure.

The empirical studies were conducted to determine if zinc and aluminum coatings sprayed with a TWEA spray system could perform as corrosion resistant coatings for INEEL site-specific applications. Once a coating is put into service, its coating performance factors are strongly controlled by the nature and extent of porosity and oxide content in the as-sprayed coating. Thus, in this study the coating designs were based on the determination of the highest corrosion resistance, minimum porosity, minimum oxide content, maximum bond strength, highest deposition efficiency, and smoothest coatings that could be obtained with the process.

The TWEA process was chosen for this application because it can produce high-purity, low-porosity coatings with high bond and interparticle strength. A Tafa, Inc. Model 9000 TWEA spray system and commercially available wire (Tafa 02Z zinc, 01T aluminum, and 02A 85Zn/15Al) were used. A pseudo-alloy (70Zn/30Al) was sprayed by using one spool of 02Z zinc and one spool of 01T aluminum.

The process parameters that were varied in the experiments included orifice diameter (blue nozzle cap = 0.95 cm (0.375 in.), green nozzle cap = 1.18 cm (0.302in.), gun pressure (P), current (A), and spray distance (SD). Air was used as the primary and shroud gas. Wire injection was internal to the gun and directed parallel to the flow. An x-y servo-manipulator ensured the standoff distance and repeatability in the experiments. The traverse x-motion rate was 40.6 cm/s (16 in. per sec). A y-step of 0.32 cm (0.125 in.) was used. Sixteen traverses per pass were used. The wire was thermal sprayed onto low carbon steel coupons, cooled by air jets on the back side. The deposition side of each coupon was grit blasted with No. 36 alumina grit prior to spraying the surface. A maximum roughness (average amplitude) of 0.005 cm (2 mil) was obtained for the substrates for the coupons used for the met mounts. A maximum roughness (average amplitude) of 0.0076 cm (3 mil) was obtained for the substrates for the coupons used for accelerated corrosion testing. The substrate roughnesses were measured with Testex, Inc. profile replica tape and a KTA Tator micrometer.

Coatings were characterized and evaluated by a number of techniques for the two wire systems. These include bond strength tests, optical metallography, image analysis, surface profilometry, and deposition efficiency. Characterization of the coatings yielded the physical, chemical, and mechanical properties of the various coatings, including thickness, bond strength, roughness, porosity, oxide content, and deposition efficiency. Attributes were measured on metallographically prepared cross-sections of each coating. Table I presents the results of the metal coating characterization.

Porosity was determined using image analysis (differential interference contrast technique). A Leco 3001 Image Analyzer with an Olympus PMG-3 metallograph was used for the metallurgical mounts. A magnification of 500´ was used to maximize contrast between the pores and the surrounding coating and to obtain sufficiently imaged pore size to ensure accuracy of results. Each coating was examined for bulk porosity at several locations and one representative area was chosen to determine the porosity for each coating. The porosities obtained from this methodology for each material are listed in Table I. The porosity of the confirmation coatings was 1.3% for aluminum, 2.8% for zinc, 2.3% for 85/15, and 3.2% for 70/30, indicating the validity of the SDE design.

The same image analysis procedure was used to measure oxide content. After the coatings were measured for porosity, the oxide content was obtained by simply subtracting the porosity value from the measured porosity plus oxide value. The oxide content of the confirmation coatings was 1.4% for aluminum, 3.3% for zinc, and 2.1% for 85/15. The oxide content of the 70/30 coatings was not able to be determined after polishing due to oxidation of the zinc phase and presence of phase boundaries.

Surface roughness was determined using a WYKO RST white light interferometer. The average roughness was calculated per ANSI standard B46.1 as the average departure ,yi, from the mean y. Average roughness ranged from 7.2 to 20.1 microns for the aluminum coatings, 4.3 to 10.2 microns for the zinc coatings, 5.9 to 9.3 microns for the 85/15 coatings, and 6.5 to 13.2 microns for the 70/30 coatings.

Deposition efficiency for selected coatings was determined with conventional techniques by measuring the amount of sprayed metal deposited for an allotted time for the optimum design coatings of the study. Deposition efficiency for the confirmation coatings was 51.3% for the aluminum, 47% for zinc, 56.2% for the 85/15 coatings, and 45.7% for the 70/30 coatings.

Bond strength measurements were conducted using a portable adhesion tester [pneumatic adhesion tensile testing instrument (PATTI)] following the test procedure described by ASTM standard D4541. The materials were sprayed onto light carbon steel substrates (4 ´ 6 ´ 0.125 inches). Each coupon was first grit blasted with No. 36 alumina grit prior to spraying the surface to obtain a surface roughness (amplitude) of 3 mils. An adhesive was then used to bond a pull stub to the coatings. This method is reported to generate quantitative tensile strength data with a 2% or better accuracy. The bond strength of the confirmation coatings using the PATTI instrument was 12.6 MPa (1834 psi) for aluminum, 7.3 MPa (1059 psi) for zinc, 7.86 MPa (1467 psi) for the 85/15 coating, and 7.86 Mpa (1140 psia) for the 70/30 coating.

Image analysis revealed differences in the microstructures for the various coatings. Based on the criteria of low porosity and oxide content, all of the metal coatings are graded as very good in quality. No cracking nor unmelted particles were evident in any of the coatings. Figure 2 illustrates the microstructure for zinc confirmation coating ZC. The coating has small pores, with homogeneous distribution. Figure 3 illustrates the microstructure for aluminum confirmation coating, AC. The coating has discernible porosity, which was homogeneously dispersed throughout the coating matrix. The AC coating has larger pores than the ZC, with more homogeneous distribution. High magnification views of the microstructures indicate differences in morphology, particle distribution, and amounts of oxide particles for the four coating systems. The zinc splat morphologies had a tendency for larger diameter and thinner lamella than the other coatings. There was a tendency for two types of lamella in the 70/30 coatings.

Laboratory testing of the test panels was accomplished to evaluate the ability of the materials to resist corrosion when subjected to a salt spray environment for 1000 hours in accordance with ASTM B117-95. Fourteen samples of each material were tested in accordance with the test matrix. The test panels were removed from the salt spray and photographed at each 100-hr interval for 900 hr. The panels were then cleaned with 10% HCL for one minute to remove salts and corrosion products from the surfaces. The panels were then evaluated for surface pitting, percentage of surface area exhibiting pitting or other corrosive activity, erosion of coating from the edges, and whether the steel substrate was exposed. The panels were then ranked in order of performance for pitting and surface area evaluation parameters and scored accordingly. Weighting factors were assigned to the evaluation parameters as follows: surface pitting, 3; surface area involved, 4; erosion from edge, 2; and steel substrate exposed, 4. The final score for the corrosion resistance (CR) is presented in Table I. The highest value of CR is the most corrosion resistant coating. The aluminum coatings CR average was 74, whereas the zinc coatings CR average was 70, indicating comparable corrosion resistances for the two materials. The 70/30 coatings CR average was 52.5, whereas the 85/15 coatings CR average was 56.4, indicating the 85/15 coatings had lower corrosion resistance than pure zinc or aluminum.

Once the experiments were conducted, the data were analyzed with the Design-Ease program for the fractional-factorial design. By using the variance of the process parameter divided by the total variance, an influence variable (%I) can be obtained, which can be used to indicate which parameters are the most influential on the coating attributes. This effects analysis dictated the final process parameters. The optimum coating was based on the highest corrosion resistance that could be obtained for each materials, with low porosity and oxide content a secondary consideration. Since bond strength had a relatively small variance, it was discounted. The smoothness of the coating was inconsequential for this application, since the metal coating will either be sealed with a paint or a polymer coating.

For the aluminum system, corrosion resistance was most influenced by spray distance. Porosity and oxide content were most influenced by pressure. The combination of the green nozzle cap, 0.55-MPa (80-psi) gun pressure, a current of 300 A, and a 7.62-cm (3-in.) spray distance is predicted to produce the most corrosion resistant aluminum coatings, with low porosity and oxide content, and intermediate roughness and bond strength. Confirmation run AC verified the design process parameters and produced a coating with the highest corrosion resistance and lowest porosity and oxide content of the series.

For the zinc system, interaction effects were evident for the corrosion resistance attribute, with only the spray distance exhibiting a significant effect. Porosity and oxide content were most influenced by pressure and nozzle diameter. The combination of the green nozzle cap, 0.55-MPa (80-psi) gun pressure, a current of 100A, and a 17.8-cm (7-in.) spray distance is predicted to produce the most corrosion resistant zinc coatings, with low porosity, low oxide content, low roughness, and intermediate bond strength. Confirmation run ZC verified the design process parameters and produced a coating with the highest corrosion resistance and lowest porosity and oxide content of the series.

For the 70/30 system, corrosion resistance was most influenced by nozzle diameter. Porosity was most influenced by pressure. The combination of the blue nozzle cap, 0.55 MPa (80-psi) gun pressure, a current of 100 A, and a 17.8-cm (7-in.) spray distance is predicted to produce the most corrosion resistant 70/30 coatings. with low porosity, intermediate roughness, and high bond strength. Confirmation run 7030C verified the design process parameters, and produced a coating with the highest corrosion resistance of the series.

For the 85/15 system, corrosion resistance was affected primarily by nozzle diameter, with current and spray distance exhibiting a significant secondary effect. Porosity and oxide content were most influenced by pressure. The combination of the green nozzle cap, 0.55 MPa (80-psi) gun pressure, a current of 100 A, and a 7.62-cm (3-in.) spray distance is predicted to produce the most corrosion resistant 85/15 coatings, with low porosity, low oxide content, low roughness, and intermediate bond strength. Confirmation run 8515C verified the design process parameters, and produced a coating with the highest corrosion resistance of the series.

The role of a polymer [9] for this application is to act as a barrier (sealant) coating for a metal coating (zinc, aluminum) applied to mitigate corrosion of metal surfaces. The original barrier action of the polymer coating layer and secondary sacrificial action of the metal layer affords separate portions of the protective ability of the total coating system. The Flame (subsonic combustion) spray process was chosen because it can produce high-purity, low-porosity polymer coatings. SDE studies of the Flame process were conducted in order to determine the quality and economics of polyester and urethane coatings. In this study, the coating designs have been optimized using fractional-factorial experiments. Optimized coating designs were achieved for the two powder systems. The coatings were characterized by optical metallography, hardness testing, tensile testing, and compositional analysis. Confirmation testing was accomplished to verify the coating designs.

Taguchi-type [10] L9 fractional-factorial experiments were conducted to determine the parameter space for optimization of the coatings. This statistical analysis was accomplished using the Sadie [11] and Design-Ease software. The designs evaluated the effect of the processing variables on the quantitatively measured responses. The following process parameters were used for the SDE experiments: oxygen to acetylene flow ratio, total flow, spray distance, and powder feedrate. The working gases were acetylene (C2H2) and oxygen.

The coatings were characterized and evaluated by a number of techniques, including hardness tests, optical metallography, image analysis, roughness, composition, deposition efficiency, and tensile testing. Characterization of the coatings yielded the thickness, bond strength, Knoop microhardness (25 gram load), roughness amplitude, porosity, and deposition efficiency. Attributes were measured on metallographically prepared cross-sections of each coating.

Deposition efficiency for the materials was determined with conventional techniques by measuring the amount of sprayed polymer deposited for an allotted time for selected experiments. The deposition efficiencies for the optimum process parameters (i.e., design coatings) were 43% for the polyester powder (run P0) and 57% for the urethane powder (run U0).

Porosity for the coatings was determined using image analysis techniques. Ten regions were evaluated to determine the percent porosity in the polymer coatings, which ranged from 1.2 to 5.1% for the polyester coatings and 0.7 to 4.4 for the urethane coatings.

Owing to the soft nature of the polymer coatings, microhardness measurements were performed using the Knoop hardness scale with a 25-gram load on the specimens. The microhardness measurements ranged from 14.9 to 17.7 for the polyester coatings and 14.2 to 23.2 for the urethane coatings.

The PATTI device was used to determine bond strength, which ranged from 1.11 to 1.96 Mpa (162 to 284 psia) for the polyester coatings and 0.56l to 2.24 MPa (81 to 325 psia) for the urethane coatings.

Surface roughness was measured with a dial depth micrometer. The coating amplitudes (peak to valley readings) were nominally 4.5 mils for the polyester coatings and 4.8 mils for the urethane coatings.

Metallographic examination and image analysis revealed differences in the microstructures of the polymer coatings. All coatings produced in this study can be graded from good to very good in quality. The photomicrographs indicate very dense coatings, with homogeneously dispersed porosity. All microstructures exhibited a totally melted coating matrix. Surface examinations revealed splat-like formations, indicating the predominance of molten conditions upon deposition. The lamallar morphologies are very similar, with perhaps a tendency for slightly rounder splats in the urethane coatings. Many polymer coatings evidenced layering, possibly because the coatings were created in four passes.

Sample P0 was the optimized design for the polyester system. Relative to the other polyester coatings, this coating had the highest porosity, the lowest hardness, intermediate deposition buildup, and very high bond strength and roughness. No macroscopic cracking (segmented cracking appearing either parallel or normal to the substrate) was apparent in the body of the coating or at the interface. Three or four distinct polymer layers are evident in the microstructure. The porosity ranged from 5 to 15 micron size pores and was dispersed homogeneously throughout the coatings.

Sample U0 was the optimized design for the urethane system. Relative to the other urethane coatings, this coating possessed low porosity, intermediate hardness and roughness, and very high bond strength and deposition buildup. Figure 4 (100´ ) illustrates the coating. No macroscopic cracking (segmented cracking appearing either parallel or normal to the substrate) was apparent in the body of the coating or at the interface. Random pores from 3 to 10 microns were discernible at a magnification of 200´ . Three or four distinct polymer layers are evident in the microstructure.

Effects analysis was first conducted for the coating responses. A quadratic design was required to predict the coating attributes for all four process parameters for the plastic coatings. Once the effects analysis was completed, the ANOVA (analysis of variance) calculations were conducted for each response for each material. In general, for all responses the comparison of the treatment variance with the error variance was good, the probability that the model terms are null was low, and the coefficient of variation (CV) was low, indicating that the error was relatively small. This analysis yielded the regression equations for each attribute. Analysis was then conducted to determine the optimum parameters for the coating designs. This methodology involved numerical optimization to search for a combination of factor levels that simultaneously satisfies the requirements placed on each of the responses. With multiple responses, one must find regions where the process parameters simultaneously meet the critical properties. By superimposing response contours, one can numerically search for a compromise optimum for the coatings. The assumptions used for the numerical optimization involved priority weighting of the attributes. The optimum derived process parameters for the polyester coating design are an oxygen-to-acetylene ratio of 2.75, a total flow of 96.3 scfh, a spray distance of 3.5 in., and a powder feedrate of 4.0 lb/hr. The optimum derived process parameters (U0) for the urethane coating design are an oxygen-to-acetylene ratio of 2.875, a total flow of 75 scfh, a spray distance of 4.6 in., and a powder feedrate of 6.0 lb/hr.

Implementation of drum refurbishment technology will provide a cost savings by avoiding retrieval of waste from the earthen-covered berms and the cost of the overpacks. Table II illustrates the costs to grit blast, metal coat, and polymer coat 55-gal drums.

Assumptions used in the cost analysis include capital equipment costs of 600K (equipment, robotics, fixturing). Each process is optimized with repeatable process parameters, hardware is robust (new) and maintained, equipment is cost effective and operating correctly, quality control methodology exists for coating and blasting repeatability, three barrels are blasted per hour, three barrels are TWEA coated per hour, and three barrels are polymer coated per hour. The cost to refurbish 1 barrel (20 minutes) is $157.30.

Experimental studies of grit blasting and thermal spraying of metal and polymer coatings were conducted to demonstrate the suitability of the systems for anti-corrosion applications at the INEEL. The coatings were characterized and evaluated by a number of techniques, including hardness tests, roughness tests, optical metallography, image analysis, and bond strength. All the coatings produced in this study may be graded from good to very good in quality. In general, the coatings had reasonable bond strength, low roughness, and good deposition efficiency. The photomicrographs indicate very dense coatings with low homogeneously dispersed porosity.

A statistical effects analysis was conducted for all of the coating attributes and the surface preparation attributes in order to optimize the designs for each system using effects and ANOVA analysis. These studies led to the final optimum process parameters that were in confirmation runs to establish the coating designs for waste applications at the INEEL.

Implementation of drum refurbishment technology will provide a cost savings by avoiding retrieval of waste from the earthen-covered berms and the cost of the overpacks. It is estimated that it will take 20 minutes to refurbish a barrel, at a cost of $157.30

1. D. Shropshire, M. Sherick, C. Biagi, Waste Management Facilities Cost Information for Mixed Low-Level Waste, Idaho National Engineering Laboratory, INEL-95/0014, June 1995.
2. Kubel, E. D., Advanced Materials and Processes, 132, 6, December 1987, pp. 69-80.
3. Whitcomb, P., et al, Design-Ease, Version 2.0, Design-Expert, Version 3.0, Stat Ease Incorporated, 2021 E. Hennepin, #191, Minneapolis, MN 55413.
4. C. G. Pfeifer, "Planning Efficient and Effective Experiments," Mechanical Engineering, May 1988, pp. 35–39.
5. G. E. P. Box, W. G. Hunter, J. S. Hunter, Statistics for Experimenters, Wiley, 1978.
6. Econoline Manual RA 36-1, Econoline Abrasive Products Division, Grand Haven, MI 49417.
7. Clemco Abrasive Blast Equipment Selection Guide, Clemco Industries, Washington, MO 63090.
8. D. Hewitt, Welding and Metal Fabrication, November 1972, pp. 382–389.
9. Engineering Plastics, ASM International, 1988.
10. G. Taguchi, and S. Konishi, Taguchi Methods: Orthogonal Arrays and Linear Graphs, ASI Press, 1987.
11. R. F Culp, Sadie, 1989.

BACK