Finite Element Simulation of Thermal Field in Submerged Arc Strip Electrode Cladding on Thick Plates

1. Definition and Technical Principles

Finite element simulation of the temperature field in submerged arc strip electrode (SASE) cladding on thick plates is a computational thermomechanical analysis methodology used to predict, optimize, and validate the transient and residual thermal behavior during heavy-overlay welding operations. Unlike conventional consumable electrode submerged arc welding (SAW), strip electrode SAW employs a continuous metallic strip—typically 0.15 mm to 0.50 mm thick and 20 mm to 40 mm wide—as the filler metal source, delivering significantly higher deposition rates (up to 8–12 kg/h compared to 2–4 kg/h for wire SAW) and enabling rapid buildup of thick overlay layers on base plates ranging from 20 mm to over 200 mm in thickness.

The finite element simulation models the coupled heat transfer, phase transformation, and residual stress evolution during multi-pass cladding using the heat equation:

ρC_p ∂T/∂t = ∇·(k∇T) + Q

where ρ is density, C_p is specific heat capacity, k is thermal conductivity, T is temperature, t is time, and Q is the volumetric heat source term representing the moving arc energy input. The simulation accounts for temperature-dependent material properties, latent heat of fusion, convection and radiation boundary conditions, and the thermal mass of thick base plates that significantly influence heat dissipation patterns compared to thin-plate applications.

2. Category and Business Positioning

This technology entry falls under the company's engineering analysis and process qualification capability domain, serving as the intellectual foundation for the following operational categories:

• Process Development & Optimization: Provides the analytical basis for designing WPS (Welding Procedure Specifications) for thick-plate cladding jobs where empirical trial-and-error is prohibitively expensive.
• WPS Qualification Support: Enables prediction of HAZ (Heat-Affected Zone) dimensions, cooling rates (t_8/5), and residual stress distributions prior to physical qualification testing.
• Customer Technical Consultation: Demonstrates analytical depth to end-users in oil & gas, power generation, and mining sectors who require assurance of cladding performance on heavy components.
• Internal Engineering Capability: Elevates the company's technical competency from purely execution-oriented welding services to integrated design-build-verify capability.

Within Cladding Technology Shanxi Co., Ltd.'s three primary technology routes—TIG/MIG weld overlay, hydraulic explosive bonding, and explosion welding—the FEA temperature field simulation primarily supports the weld overlay route but also provides complementary analytical value for the explosive cladding routes by informing post-explosion stress-relief annealing parameters and interface temperature predictions.

3. Technical Purpose and Value

3.1 Primary Engineering Objectives

The finite element simulation of SASE cladding thermal fields serves the following critical engineering purposes:

1. Deposition Rate Optimization: Determine the maximum achievable single-pass deposition thickness while maintaining acceptable cooling rates to prevent cracking in high-carbon equivalent base metals.
2. Interpass Temperature Control: Predict optimal interpass temperature windows (typically 150°C–350°C for austenitic overlays, 50°C–250°C for martensitic overlays) to balance productivity with metallurgical quality.
3. Residual Stress Prediction: Quantify thermal residual stresses that may compromise dimensional stability or service performance of clad components.
4. Crack Susceptibility Assessment: Identify regions of peak thermal gradient and tensile stress where hot cracking, cold cracking, or reheat cracking are most likely.
5. Thermal Cycle Characterization: Generate accurate cooling rate profiles (t_8/5, t_8/3) for microstructural prediction and HAZ hardness mapping.

3.2 Quantifiable Value to Operations

• Reduces physical trial welding by 60–80% during new procedure development, saving 50–200 labor hours per WPS qualification.
• Enables predictive process windows that reduce rework rates by an estimated 30–50% on thick-plate production jobs.
• Provides documented analytical evidence for customer audits and third-party inspection agencies.
• Accelerates time-to-market for custom cladding solutions on non-standard geometries.

4. Key Process and Implementation Points

4.1 Simulation Model Configuration

Accurate thermal field simulation of SASE cladding on thick plates requires careful configuration of the following model elements:

Model Parameter	Typical Range / Setting	Engineering Rationale
Element Type	3D solid (brick), 8-node or 20-node	Captures through-thickness thermal gradients in plates >20 mm
Element Size (near weld line)	1.0–2.0 mm	Resolves steep thermal gradients in weld bead and HAZ
Element Size (far field)	5.0–10.0 mm	Reduces computational cost without sacrificing accuracy
Heat Source Model	Double-ellipsoidal (Goldak) or cylinder	Represents asymmetric heat distribution of strip arc
Heat Input	40–120 kJ/cm	Typical SASE range for 15–60 mm plate thickness
Boundary Conditions	Convection (h=25–75 W/m²·K) + Radiation (ε=0.8–0.95)	Models air cooling and oxide scale radiation losses
Material Properties	Temperature-dependent k(T), ρ(T), Cp(T)	Critical for austenitic, martensitic, and duplex overlay alloys
Latent Heat Treatment	Enthalpy method or effective Cp method	Accurately captures solidification behavior
Weld Travel Speed	0.5–3.0 m/min	Depends on strip width, wire feed rate, and target bead profile

4.2 Strip Electrode SAW Process Parameters for Thick Plate

Parameter	Typical Value (Thick Plate >20 mm)	Notes
Strip Width	25–40 mm	Wider strips enable greater single-pass deposition
Strip Thickness	0.15–0.30 mm	Thinner strips provide better arc stability
Wire Feed Rate	8–20 m/min	Higher rates increase deposition; must match arc length
Current	800–1600 A (DCEN)	DCEN provides deeper penetration; DCEP gives shallower, wider bead
Arc Length	1.5–4.0 mm	Critical for arc stability with strip electrodes
Flux Coverage	Full submerged, 8–15 mm flux depth	Protects molten pool; flux type per WPS
Travel Speed	0.5–2.5 m/min	Inversely proportional to deposition thickness per pass
Interpass Temperature	150–350°C (austenitic); 50–250°C (martensitic)	Controlled to manage cooling rate and residual stress
Preheat Temperature	100–300°C (depends on PCM and CE)	Reduces HAZ hardness; minimizes cracking risk

4.3 Multi-Pass Thermal Accumulation Modeling

Thick-plate cladding typically requires multiple passes to build the overlay layer to specification (commonly 3–10 mm total overlay thickness). The simulation must account for thermal accumulation across successive passes:

• Single-pass model: Establishes baseline thermal profile for the first layer deposited on the base plate.
• Sequential multi-pass model: Superimposes subsequent passes with appropriate time delays, capturing the progressive warming of previously deposited material and the altered thermal boundary conditions.
• Full-buildup model: Simulates the complete cladding sequence including groove preparation, root pass, fill passes, and cap pass, providing final residual stress and distortion predictions.

4.4 Critical Analysis Outputs

The simulation yields the following actionable outputs that directly inform production decisions:

1. Peak temperature distribution: Identifies zones exceeding solidus temperature of the base metal, indicating potential dilution and microstructural alteration.
2. Cooling rate maps (t_8/5): Enables prediction of HAZ microstructure—coarse grain zone formation above t_8/5 < 5 s, martensitic transformation in high-CE steels above t_8/5 < 10 s.
3. Residual stress tensor field: Quantifies longitudinal, transverse, and through-thickness stresses to assess distortion risk and need for stress-relief heat treatment.
4. Thermal distortion prediction: Forecasts angular and longitudinal distortion of the cladded component for fixture design and post-weld straightening planning.
5. Optimal interpass temperature window: Provides data-driven justification for maximum permissible interpass temperatures that maintain metallurgical integrity.

5. Applicable Standards and Acceptance Criteria

5.1 Welding Procedure Standards

Standard	Relevance to SASE Cladding Thermal Simulation
ASME Section IX	WPS/PQR qualification requirements; essential variables include heat input, preheat, and interpass temperature—all validated through simulation
GB/T 19866 (ISO 15614-1)	Qualification testing for welding procedures for metallic materials; thermal cycle characterization requirements
NB/T 47014 (JB/T 4708)	Chinese national standard for WPS qualification in pressure equipment; thermal parameters and essential variable definitions
API 571 / API 579	Fitness-for-service assessment; residual stress predictions inform remaining life evaluation of cladded components
ISO 13919 (SAW processes)	Defines process parameters and terminology for submerged arc welding including strip electrode variants
EN ISO 9606	Welder/operator qualification requirements; thermal parameters within qualified range

5.2 Material and Performance Standards

• ASTM A240 / A268: Overlay material specifications (austenitic stainless steels 304L, 309L, 310L, 316L)
• ASTM A387 / A516: Base plate specifications (Cr-Mo and carbon steel plates for cladding)
• ASTM A743 / A744: Nickel-base alloy overlay specifications (Inconel 625, Hastelloy C-276)
• GB/T 17748: Chinese standard for clad steel plates (including weld overlay products)
• NACE SP0169: Corrosion control; informs overlay thickness requirements for cathodic protection

5.3 Simulation Validation Acceptance Criteria

For simulation results to be accepted as valid engineering input, the following validation benchmarks must be met:

1. Peak temperature deviation: Simulated vs. measured (thermocouple or thermography) peak temperature within ±15% or ±100°C, whichever is greater.
2. Cooling rate deviation: Predicted t_8/5 within ±30% of experimentally determined values from thermal imaging or embedded thermocouples.
3. Residual stress deviation: Predicted longitudinal residual stress within ±50 MPa of X-ray or neutron diffraction measurements.
4. Distortion deviation: Predicted angular distortion within ±0.5 mm/m of post-weld dimensional measurements.

6. Common Risks and Controls

Risk Category	Description	Simulation-Based Control
Hot Cracking	Solidification cracking in high-deposition-rate SASE passes, particularly in sulfur/phosphorus-sensitive alloys	Identify peak thermal gradient zones and tensile stress regions; optimize travel speed and heat input to reduce solidification range
Cold Cracking (Hydrogen-Induced)	Delayed cracking in high-CE base metals due to rapid cooling and hydrogen accumulation	Predict t8/5 < 10 s zones; prescribe adequate preheat and post-weld heat treatment based on simulation outputs
Excessive Dilution	Base metal dilution into overlay reducing corrosion resistance (critical for Ni-base and austenitic overlays)	Model heat input distribution to predict dilution zone; recommend lower heat input or multiple thinner passes
Residual Stress Exceedance	Thermal residual stresses exceeding material yield strength causing distortion, cracking, or fatigue degradation	Quantify stress fields; prescribe stress-relief annealing parameters (temperature, time, cooling rate) to reduce stresses below allowable limits
Thermal Distortion	Warping of thick plates exceeding flatness tolerances (typically <1.5 mm/m for pressure vessel shells)	Predict distortion magnitude and direction; design restraining fixtures and post-weld straightening procedures
HAZ Hardness Exceedance	Martensitic transformation in HAZ of Cr-Mo steels producing hardness >350 HV	Map t8/5 distribution; prescribe preheat levels and PWHT to achieve acceptable HAZ microstructure
Interpass Overheating	Excessive interpass temperatures causing grain growth, sigma phase formation, or loss of strength	Calculate thermal accumulation across passes; define maximum permissible interpass temperature for each alloy system

7. Application Across the Company's Three Technology Routes

7.1 TIG/MIG Weld Overlay (Primary Application)

Finite element temperature field simulation is most directly applicable to the company's TIG (GTAW) and MIG (GMAW) weld overlay operations, complementing the SASE process analysis:

• Transition layer design: Simulates thermal cycles for dissimilar metal transitions (e.g., carbon steel to 309L to 316L overlay), predicting dilution and microstructural evolution.
• Multi-layer build-up optimization: For overlay thicknesses of 1–5 mm using TIG/MIG, the simulation determines optimal layer thickness, interpass temperature, and thermal cycle parameters.
• Small-diameter component analysis: For pipe and tube cladding where heat dissipation is more complex than flat plates, 3D thermal modeling captures circumferential and axial temperature distributions.
• Low-heat-input process validation: TIG overlay typically uses 10–30 kJ/cm heat input; simulation validates that cooling rates remain within acceptable ranges for crack-sensitive alloys.

7.2 Hydraulic Explosive Bonding (Complementary Application)

While hydraulic explosive bonding (water-jet-assisted explosion welding) does not involve a welding arc, thermal simulation provides critical supporting analysis:

• Post-bonding thermal stress assessment: Predicts residual thermal stresses in the base and cladding materials following the high-strain-rate bonding event, informing stress-relief procedures.
• Interface temperature estimation: Models the adiabatic shear heating at the bonding interface to assess metallurgical bonding quality and interface microstructure.
• Post-processing heat treatment design: Determines optimal annealing parameters for stress relief and interface stabilization following the bonding operation.
• Multi-layer bonding sequence planning: For sequential bonding of multiple layers, thermal accumulation between bonds is modeled to prevent excessive residual stress.

7.3 Explosion Welding (Complementary Application)

In conventional explosion welding (air-gap or water-gap), thermal simulation contributes to the following analyses:

• Preheating optimization: For thick-plate explosion welding, base plate preheating (typically 200–400°C) is used to enhance bonding quality; simulation determines optimal preheat temperature and distribution.
• Post-explosion thermal stress prediction: The rapid cooling from preheat temperature creates significant thermal gradients; simulation quantifies resulting residual stresses.
• Subsequent weld repair analysis: When explosion-welded interfaces require localized repair welding, thermal simulation of the repair weld on a pre-stressed substrate ensures sound repair procedures.
• Thermal compatibility assessment: For dissimilar material pairs (e.g., carbon steel/Al, steel/titanium), thermal expansion mismatch during post-explosion cooling is modeled to predict interface stress.

8. Contribution to Qualification Building, Product Delivery, and Customer Value

8.1 Qualification Building

The finite element simulation capability directly strengthens the company's qualification portfolio in the following ways:

1. WPS Rationalization: Provides analytical justification for selected process parameters, reducing the number of physical PQR (Procedure Qualification Records) required to cover production ranges.
2. Essential Variable Coverage: Demonstrates understanding of how heat input, preheat, and interpass temperature affect weld quality—key essential variables in ASME IX, GB/T 19866, and NB/T 47014.
3. Third-Party Audit Support: Provides documented analytical evidence for audits by ASME, NQA-1, API Q1, or ISO 3834 inspectors evaluating the company's welding quality system.
4. Novel Procedure Development: Enables qualification of new overlay combinations (e.g., duplex stainless on Cr-Mo steel) through simulation-verified procedures before committing to expensive physical testing.

8.2 Product Delivery Enhancement

• Reduced rework: Predictive thermal analysis minimizes the probability of cracking, excessive hardness, or distortion that would require costly rework or rejection.
• Optimized production scheduling: Simulation outputs enable precise interpass temperature monitoring protocols, reducing cycle time while maintaining quality.
• Fixture and restraint design: Distortion predictions inform the design of welding fixtures that minimize post-weld straightening requirements.
• Quality traceability: Simulation records provide a complete analytical trail for each production batch, supporting quality traceability requirements.

8.3 Customer Value Delivery

For end-users in the oil & gas, power generation, mining, and chemical processing industries, this simulation capability delivers the following value propositions:

1. Performance assurance: Customers receive analytically verified overlay designs with predicted service life based on validated thermal and stress models.
2. Accelerated project timelines: Reduced trial-and-error shortens project schedules by 20–40% for complex thick-plate cladding jobs.
3. Technical partnership credibility: Demonstrates engineering sophistication that differentiates the company from purely execution-oriented welding contractors.
4. Cost optimization: Simulation-guided process optimization reduces material consumption (overlay alloy), labor hours, and post-weld processing requirements.
5. Compliance documentation: Provides simulation reports that satisfy customer specification requirements for analytical process validation (increasingly required by major EPC contractors).

9. Implementation Recommendations

To maximize the return on this technical capability, the following implementation steps are recommended:

1. Software platform: Utilize industry-standard FEA tools (ANSYS Mechanical, ABAQUS, or DEFORM-Welding) with validated welding heat source modules.
2. Material database: Maintain a comprehensive temperature-dependent material property database for all base and overlay alloys in production use, sourced from vendor data sheets and validated by DSC/Dilatometry.
3. Validation protocol: Establish a systematic validation program comparing simulation predictions against instrumented trial welds (thermocouple arrays, thermography, strain gauges, X-ray stress measurement).
4. Integration with production: Develop simplified simulation workflows that production engineers can execute for routine thick-plate jobs without requiring full research-grade analysis.
5. Knowledge transfer: Document simulation methodologies, assumptions, and limitations in internal technical manuals accessible to all engineering and production staff.
6. Continuous improvement: Update simulation models with feedback from production outcomes (rework rates, NDT results, service performance data) to progressively improve prediction accuracy.

10. Conclusion

Finite element simulation of the temperature field in submerged arc strip electrode cladding on thick plates represents a critical intellectual asset for Cladding Technology Shanxi Co., Ltd. It bridges the gap between empirical welding practice and rigorous engineering analysis, enabling the company to deliver higher-quality, more reliable, and more cost-effective cladding solutions. By integrating this analytical capability with the company's three core technology routes—weld overlay, hydraulic explosive bonding, and explosion welding—the organization positions itself as a technically sophisticated, qualification-ready partner capable of addressing the most demanding thick-plate cladding challenges in heavy industry. The simulation capability transforms the company from a welding execution service into a full-spectrum cladding engineering partner, directly enhancing customer confidence, qualification credentials, and competitive differentiation in the industrial cladding market.