[Paper Review] Contact.engineering-Create, analyze and publish digital surface twins from topography measurements across many scales

Michael Clemens Röttger, Antoine Sanner+7 more|arXiv (Cornell University)|Mar 25, 2022

Adhesion, Friction, and Surface Interactions93 references36 citations

TL;DR

This paper presents contact.engineering, an open-source, web-based platform that creates digital surface twins by integrating multi-scale topography measurements from various instruments. It enables automated spectral analysis, mechanical modeling (e.g., BEM for elastic/plastic contact), and FAIR-compliant data sharing with DOIs, addressing key challenges in surface metrology: multi-scale integration, technical complexity, and data inconsistency.

ABSTRACT

The optimization of surface finish to improve performance occurs largely through trial and error, despite significant advancements in the relevant science. There are three central challenges that account for this disconnect: (1) the challenge of integration of many different types of measurement for the same surface to capture the multi-scale nature of roughness; (2) the technical complexity of implementing spectral analysis methods, and of applying mechanical or numerical models to describe surface performance; (3) a lack of consistency between researchers and industries in how surfaces are measured, quantified, and communicated. Here we present a freely-available internet-based application which attempts to overcome all three challenges. First, the application enables the user to upload many different topography measurements taken from a single surface, including using different techniques, and then integrates all of them together to create a digital surface twin. Second, the application calculates many of the commonly used topography metrics, such as root-mean-square parameters, power spectral density (PSD), and autocorrelation function (ACF), as well as implementing analytical and numerical calculations, such as boundary element modeling (BEM) for elastic and plastic deformation. Third, the application serves as a repository for users to securely store surfaces, and if they choose, to share these with collaborators or even publish them (with a digital object identifier) for all to access. The primary goal of this application is to enable researchers and manufacturers to quickly and easily apply cutting-edge tools for the characterization and properties-modeling of real-world surfaces. An additional goal is to advance the use of open-science principles in surface engineering by providing a FAIR database where researchers can choose to publish surface measurements for all to use.

Motivation & Objective

• Address the lack of integration across multi-scale topography measurements from diverse instruments (e.g., stylus profilometry, AFM).
• Overcome the technical complexity of spectral analysis and mechanical modeling (e.g., BEM) for non-expert users.
• Standardize surface characterization and data sharing to improve reproducibility and interoperability across research and industry.
• Enable researchers and manufacturers to predict surface performance (e.g., friction, adhesion) using advanced models on real-world surface data.
• Advance open science in surface engineering by providing a FAIR-compliant platform for publishing and citing surface data with DOIs.

Proposed method

• Integrates multiple topography measurements (e.g., line scans, 2D maps) from different instruments into a single, multi-scale digital surface twin.
• Uses a Python-based computational engine (SurfaceTopography and ContactMechanics) for standardized analysis of surface metrics and mechanical models.
• Automatically computes key metrics: root-mean-square parameters, power spectral density (PSD), autocorrelation function (ACF), and performs boundary element method (BEM) simulations.
• Employs a Django-based web interface (TopoBank) with PostgreSQL for data management and Celery task queue for asynchronous, scalable analysis execution.
• Stores data securely with georedundant storage (NetApp StorageGRID) and supports public sharing with persistent DOIs for citable publication.
• Supports parameterized analyses with caching to avoid redundant computation, and allows users to override default analysis settings.

Experimental results

Research questions

• RQ1 How can multi-scale topography data from diverse instruments be seamlessly integrated into a unified digital surface twin?
• RQ2 To what extent can automated spectral and mechanical analysis reduce the technical barrier to applying advanced surface characterization models?
• RQ3 Can a standardized, FAIR-compliant platform improve data sharing, reproducibility, and reuse in surface engineering research and industry?
• RQ4 How does the integration of multi-scale data improve the accuracy of performance predictions (e.g., contact mechanics, friction, wear) compared to single-scale measurements?
• RQ5 What is the impact of standardized data publication with DOIs on the adoption of open science principles in surface metrology?

Key findings

• The platform successfully integrates topography data from multiple instruments and scales into a single, coherent digital surface twin, enabling comprehensive multi-scale characterization.
• Spectral analysis (PSD, ACF) and mechanical modeling (BEM for elastic and plastic deformation) are automated and accessible via a user-friendly web interface, reducing implementation barriers.
• Users can securely store, share, and publish digital surface twins with persistent DOIs, enabling citable, FAIR-compliant data sharing.
• The system caches analysis results to avoid redundant computation, and parameterized analyses are re-run only when new parameter sets are specified.
• The platform is freely accessible at https://contact.engineering and includes open-source code, supporting integration into external workflows.
• The service is actively developed and aims to extend to include chemical composition and roughness evolution models in the future, moving toward a complete digital surface twin.