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A Bayesian optimization approach for reliability-based design of prestressed concrete structures

James Whiteley; Jurgen Becque

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

This paper presents a reliability-constrained Bayesian optimization framework for structural design under uncertainty, addressing challenges in stochastic optimization where the objectives and constraints are defined implicitly by potentially expensive numerical models. Our approach explicitly…

A novel adaptive sampling approach with batch selection for the automatic generation of surrogate models in geotechnical engineering

Yunxiang Yang; Agustín Ruiz López; Aikaterini Tsiampousi dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Surrogate models have gained widespread popularity for their effectiveness in replacing computationally expensive numerical analyses, particularly in scenarios such as design optimization procedures, requiring hundreds or thousands of simulations. While one-shot sampling methods—where all samples…

A robust generalized deep monotonic feature extraction model for label-free prediction of degenerative phenomena

Panagiotis Komninos; Thanos Kontogiannis; Nick Eleftheroglou dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Addressing and predicting degenerative phenomena in domains such as health care and engineering, two fundamental fields of vital importance for society, offers valuable insights into early warning steps and critical event forecasting, leading to far-reaching implications for safety and resource…

Can time-series foundation models perform building energy management tasks?

Ozan Baris Mulayim; Pengrui Quan; Liying Han dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Building energy management (BEM) tasks require processing and learning from a variety of time-series data. Existing solutions rely on bespoke task- and data-specific models to perform these tasks, limiting their broader applicability. Inspired by the transformative success of Large Language Models…

Denoising image point clouds using segmentation and synthetic data for enhanced structural health analysis of tunnels

Ran Zhang; Wei Lin; Chao Wang dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Point clouds derived from UAV photogrammetry are a cost-effective alternative to LiDAR for infrastructure inspections, but they often include both structural and non-structural elements that complicate analysis. Traditional denoising filters remove outliers indiscriminately and frequently erode…

Embedded model form uncertainty quantification with measurement noise for Bayesian model calibration

Daniel Andrés Arcones; Martin Weiser; Phaedon-Stelios Koutsourelakis dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Bayesian methods provide a robust framework for quantifying and propagating the uncertainties that…

Domain-specific prediction of punching shear capacity in slab-column connections using explainable XGBoost models and SHAP analysis

Arslan Qayyum Khan; Mehboob Rasul; Amorn Pimanmas

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Punching shear failure in slab-column connections is a brittle collapse mode that threatens the safety of flat reinforced concrete (RC) slabs. Conventional design provisions are generally conservative but exhibit inconsistencies across geometric and material variations. This study develops an…

Principal component analysis and K-means clustering of fuel–air mixing in gas turbine combustors

David I. Salvador-Jasin; A. Duncan Walker; Jon F. Carrotte

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

As a direct consequence of liquid kerosene injection, aeroengine combustors may be categorized as non-premixed combustion systems, characterized by a swirl-stabilized and highly complex flow field. In addition to the flow of air through the fuel injector, there are a large number of other features…

Reconstruction of three-dimensional turbulent flows from sparse and noisy planar measurements: a weight-sharing neural network approach

Yaxin Mo; Luca Magri

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

This paper proposes a method for reconstructing three-dimensional turbulent flows from sparse measurements without the need for ground truth data during training. A weight-sharing network is developed to infer the full flow fields from measurements of velocity sampled at three planes and boundary…

A data assimilation and machine learning approach for the numerical prediction of immersed bodies in oscillating motion

Miguel Martínez Valero; Marcello Meldi

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Data-driven methods have demonstrated strong predictive capabilities in fluid mechanics, yet most current applications still focus on simplified configurations, often characterized by statistical stationarity or limited temporal variability. This work proposes a methodology that combines data…

Neural delay differential equations: learning non-Markovian closures for partially known dynamical systems – CORRIGENDUM

Thibault Monsel; Emmanuel Menier; Onofrio Semeraro dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

A GAN-based framework for generating STFT spectrograms of rare acoustic events in structural health monitoring

Sasan Farhadi; Mariateresa Iavarone; Mauro Corrado dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Structural health monitoring plays a crucial role in ensuring the safety, reliability, and longevity of bridge infrastructures through early damage detection. Although recent advances in deep learning-based models have enabled automated event detection, their performance is often limited by data…

Pairwise interactions in turbulence time series: essential measures for validating synthetic data

Saleh Rezaeiravesh; Daniele Massaro; Philipp Schlatter

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

The synthesis of turbulence dynamics using machine learning, statistical, and dynamical system-based models has become an emerging research direction. Validation of synthetic turbulence time series is often based on marginal and second-order statistics, which may overlook whether the underlying…

A hierarchical Bayesian approach for time-varying (possible multiple setups) finite element model updating

Mingzhu Chen; Binbin Li; Armen Der Kiureghian dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

The Bayesian approach offers a systematic framework for updating finite element (FE) models and quantifying the remaining uncertainty given measured data. However, an inappropriate formulation of the probabilistic model can compromise accuracy. This paper presents an improved hierarchical Bayesian…

Laboratory demonstration of digital twin construction

Timson Yeung; Sivan Grodsky; Jiyuan Li dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Digital Twin Construction (DTC) is a data-centric mode of construction that leverages digital twin technologies to maintain a continuously updated representation of a project and to enable short cycle Plan Do Check Act (PDCA) planning and control with continuous feedback and improvement. Industrial…

Nonlinear system identification for model-based control of waked wind turbines

Sebastiano Randino; Lorenzo Schena; Nicolas Coudou dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

This work presents a nonlinear system identification framework for modeling the power extraction dynamics of wind turbines, including both freestream and waked conditions. The approach models turbine dynamics using data-driven power coefficient maps expressed as combinations of compact radial basis…

Human–machine teaming for leisure motorboat layout design

Thomas Savasta; Bill Edwards; Adam Sobey

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Space utilization is a key driver for yacht design. Larger hulls increase the cost of the yacht substantially, and so space is always at a premium. The designs should feel spacious and luxurious, making the best use of the available volume while also conforming to standard engineering constraints…

An end-to-end PyTorch interface for differentiable PDE solvers: A RANS model-correction study

Luca Saverio; Michele Alessandro Bucci; Gianmarco Farro dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

This work presents an end-to-end strategy for solving inverse problems constrained by Partial Differential Equations within a fully differentiable Machine Learning framework. The proposed formulation provides a unified and user-friendly methodology applicable to a wide range of problems, from data…

FloorPulse: Heart rate measurement at a distance using indirect floor vibrations

Jesse R. Codling; Julia Gersey; Jeffrey D. Shulkin dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Heart rate is one of the most commonly used metrics for human health. Measuring human heart rate typically involves direct body contact, whether from wearable devices or manual measurement. However, such devices can cause discomfort in some patients, particularly in sensitive populations where such…

Benchmarking for nonlinear system identification: Submission platform and baseline results

Maarten Schoukens; Max Champneys; Gerben Izaak Beintema dkk.

Data-Centric Engineering, Vol. 7 · 2026 · Inggris · DOAJ Scopus

Benchmarking identification methods is essential to validate newly proposed algorithms. The machine learning community has illustrated how benchmarks can be a driver for new developments in the field. However, thorough benchmarking is not commonplace in the system identification literature, and…