Paton Mathematical Modelling Facility for Welding and Special Electrometallurgy

Paton Mathematical Modelling Facility for Welding and Special Electrometallurgy provides computational modelling, numerical analysis and software-supported assessment of welding, surfacing, heat treatment, additive manufacturing and special electrometallurgy processes. The facility supports modelling of heat and mass transfer, microstructure formation, thermoviscoplastic deformation, residual stresses, welding distortions, structural integrity and service-life-related behaviour of welded structures. The facility is based on the expertise of the Department of Mathematical Methods for the Investigation of Physicochemical Processes in Welding and Special Electrometallurgy at the E. O. Paton Electric Welding Institute of NAS of Ukraine. It complements experimental welding and materials testing resources by providing computational workflows, finite-element modelling, engineering assessment tools and interpretation of process-structure-property relationships.

Typical users

Typical users include researchers, engineers, PhD students, industrial R&D teams and project consortia working with welding, surfacing, heat treatment, friction stir welding, wire arc additive manufacturing, special electrometallurgy, pipelines, pressure vessels, nuclear-energy components, aerospace structures, transport structures and other critical welded systems. The facility is relevant for users who need computational support for predicting residual stresses, welding distortions, thermal cycles, stress-strain state, heat-affected zone behaviour, post-weld heat treatment effects, defect acceptability, service-life-related performance, or the influence of technological parameters on welded joint quality. It is also suitable for users who need modelling workflows for digital twins, AI-supported welding process optimization, weld quality assessment, monitoring of critical welded structures, and preparation of reusable computational datasets for research, reporting or publication.

Data outputs

Typical data outputs may include computational input files, finite-element models, mesh files, material-property tables, thermal-cycle data, temperature fields, stress and strain fields, residual stress distributions, welding distortion predictions, deformation maps, phase or microstructure-related indicators, defect assessment results, service-life-related indicators, post-weld heat treatment simulations, plots, calculation logs and short technical reports. For process modelling tasks, outputs may include temperature-time curves, heating and cooling rates, heat-source parameters, friction stir welding thermal fields, diffusion profiles, component concentration distributions, process-parameter studies and comparison with available experimental data. For reusable computational workflows, outputs may also include workflow descriptions, scripts, software settings, model assumptions, provenance notes, README documentation and metadata needed for verification, reuse or repository deposition.

Access notes

Access is provided on request and should be agreed with the responsible modelling team before the work starts. The facility should be treated as a collaborative computational modelling and engineering assessment facility rather than as an open self-service software portal. Users are expected to provide a clear description of the engineering or research problem, material system, welding or heat-treatment process, geometry, available experimental data, boundary conditions, target properties and expected outputs. For structural assessment tasks, users should provide information on joint type, dimensions, loading conditions, service conditions, detected or assumed defects, and required assessment criteria. The scope of modelling, software environment, input data, assumptions, computational resources, validation data, data formats, confidentiality conditions, authorship or acknowledgement rules and delivery timeline should be agreed in advance. If the work requires integration with experimental resources such as GLEEBLE, MTS, residual stress measurements or non-destructive testing data, the access route should be agreed as a combined experimental-computational workflow.

Related resources

Services using this facility

Used in pilot chains

• Welding process testing and modelling