Publications
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Human-Humanoid collaboration in manufacturing opportunities and challenges in the context of industry 5.0
The introduction of humanoid robots in industry represents an important aspect of the industry 5.0 enhance resilience of productin and represents a real change in the manner of dealing with the technology assistance for human operators, where the smart system will be able to execute similar tasks as the humans. This paper presents a concise […]
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Reliability based design optimization for multiaxial fatigue damage analysis using Matsubaraˆas criterion developed in the frequency domain of structures under random vibrations
This study aims to an optimal design of a structure subject to random vibrations, considering fatigue damage, that guarantees a required reliability level under uncertainties parameters. In practical applications, structures are exposed to multiaxial random loading. While numerous fatigue life prediction criteria have been developed primarily in the time domain, frequency domain methods are preferred […]
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BI2PV Simulator for Optimized BIPV Design in Industrial Buildings
The integration of photovoltaics (PV) into industrial buildings remains inhibited by the lack of unified tools that reconcile architectural constraints, energy performance, and economic viability. We present Industrial Building Integrated PV (BI²PV) simulator, an interactive simulator developed with MATLAB App Designer, encompassing the entire workflow: import and interpolation of NSRDB (National Solar Radiation Database) data […]
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Sparse space-heterogeneous, physics-constrained PDE reconstruction for defect identification through low-frequency mechanics
This contribution explores an application of automatic PDE identification for nondestructive testing. Defect localization is traditionally performed via the identification of the spatial distribution of a well-chosen physical property, which is assumed to be impacted by the defect in question. Defects whose impact on physical properties is unclear may thus cause the identification approach to […]
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Towards Eco-Efficient AI: Hybrid Data Strategies for BIPV Energy Prediction
Accurate prediction of energy production from building-integrated photovoltaic (BIPV) systems is essential for optimizing building energy use and supporting decarbonization strategies. Synthetic data provides a valuable foundation for model development, particularly when real measurements are limited, but validation on operational systems remains critical for reliable deployment. In this study, we propose a hybrid data approach, […]
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Potential of Generative Artificial Intelligence in Knowledge-Based Predictive Maintenance for Aircraft Engines
Predictive maintenance based on remaining useful life (RUL) estimation is widely recognized as a promising strategy for monitoring the health of critical systems such as aircraft engines, anticipating failures, and optimizing maintenance planning. A variety of approaches have been proposed in the literature, including data-driven, physics-based, and knowledgebased methods. Among them, deep learning-based methods have […]
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Industrial Metaverse Architecture in the Automotive Sector
The transition from Industry 4.0 to Industry 5.0 aims to develop production systems that are more people-centered, sustainable, and resilient. An emerging concept that supports this evolution is the Industrial Metaverse, which integrates technologies such as the Industrial Internet of Things (IIoT), Big Data, and virtual environments to bridge physical and digital worlds. As this […]
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A Hybrid Approach to Building Thermal Modeling Using Physics-Based Machine Learning
Buildings account for approximately 30% of primary energy consumption, mainly due to Heating, Ventilation, and Air Conditioning (HVAC) systems. Reactive controllers can be used to manage these systems optimally, however, their performance depends strongly on the accuracy of building thermal models. In this study, a hybrid physics-informed machine learning (PIML) approach is proposed to improve […]
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On-Policy vs. Off-Policy HVAC Control: Comparing PPO and SAC–Gumbel in EnergyPlus
We compare two reinforcement learning methods for HVAC control in a university amphitheater simulated in EnergyPlus: Proximal Policy Optimization (PPO, on-policy) and SAC-Gumbel (off-policy). We run two experiments. First, a weekly adaptation test trains each agent for 50 episodes using the first week of January in Luxembourg. Second, a year-long generalization test trains on a […]
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Bio-stabilised earthen materials: a perspective on the potential contribution to climate change adaptation and mitigation
With its potential for low embodied carbon, bio-stabilised earth offers a sustainable alternative to traditional carbon-intensive building materials. Moreover, unlike lime and cement stabilisation, bio-stabilisation methods hold the promise to improve the durability of earthen materials while retaining their moisture buffering capacity and recyclability. Despite the promising characteristics of bio-stabilised earth, research on the topic […]
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Combining Client-Based Anomaly Detection and Federated Learning for Energy Forecasting in Smart Buildings
In today’s interconnected world, energy consumption forecasting faces challenges due to client-side anomalies in time-series data. Federated Learning (FL) offers a decentralized solution by forecasting without directly accessing user data. However, the effectiveness of the global model can decline if local anomalies are not properly managed. We propose our lightweight framework EIF-FL: Elliptic envelope and […]
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DistillH-Mamba: A Hypergraph-Mamba-Based Knowledge Distillation Model for Efficient Impact Fall Detection
Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning has improved fall detection, accurately identifying impact moments (when an individual hits the ground) remains challenging. Additionally, current algorithms often rely on complex models with high computational demands, limiting real-time deployment feasibility. In this […]