Industry 4.0 has embraced process models in recent years, and the use of model-based digital twins has become even more critical in process systems engineering, monitoring, and control. However, the reliability of these models depends on the model pa...
This report explores the integration of problem-based learning, gamification, and data-driven approaches in engineering education. With a focus on the course “GeoGovernment 1”, this framework aimed to engage students actively and foster s...
In-cylinder pressure is a key parameter for assessing marine engines health; therefore, its measurement or prediction is paramount for these engines’ diagnosis. Thermodynamic models are typically employed for predicting the in-cylinder pressure...
Foundational algorithm instruction at the elementary level has centered on understanding control structures and reproducing given procedures; opportunities for learners to generate strategies and judge efficiency under varying data conditions remain...
The linear parameter-varying (LPV) model is widely used in aero engine control system design. The conventional local modeling method is inaccurate and inefficient in the full flying envelope. Hence, a novel online data-driven LPV modeling method base...
Condition monitoring of components in internal combustion engines is an essential tool for increasing engine durability and avoiding critical engine operation. If lubrication at the crankshaft main bearings is insufficient, metal-to-metal contacts be...
The marine engine is a complex-structured multidisciplinary system that operates in a harsh environment involving high temperatures and pressures and gas/fluid/solid interactions. Many malfunctions and faults can occur to the marine engine and effici...
Predicting Remaining Useful Life (RUL) of systems has played an important role in various fields of reliability engineering analysis, including in aircraft engines. RUL prediction is critically an important part of Prognostics and Health Management (...
Collaboration among individuals with diverse skills and personalities is crucial to producing high-quality software. The success of any software project depends on the team’s cohesive functionality and mutual complementation. This study introdu...
Reactivity controlled compression ignition (RCCI) is a highly efficient and clean combustion concept, which enables the use of a wide range of renewable fuels. Consequently, this promising dual fuel combustion concept is of great interest for realizi...
Diesel engines serve as critical power sources across transportation and industrial fields, and their fault diagnosis is essential for ensuring operational safety and system reliability. However, acquiring sufficient and effective operational data re...
Accurately predicting the remaining useful life (RUL) of the turbofan engine is of great significance for improving the reliability and safety of the engine system. Due to the high dimension and complex features of sensor data in RUL prediction, this...
This study investigates the ultimate bearing capacity of engineered bamboo columns of varying lengths under eccentric loading using a data-driven machine learning (ML) approach. Although previous studies have investigated engineered bamboo columns un...
In this paper, a methodology based on data-driven models is developed to predict the NOx emissions of an internal combustion engine using, as inputs, a set of ECU channels representing the main engine actuations. Several regressors derived from the m...
Design processes are always in motion, since more and more data-driven methods are used for various design and validation tasks. However, small and medium enterprises especially struggle with enhancing their processes with data-driven methods due to...
The accurate estimation of helicopter engine power is crucial for ensuring operational performance and maintaining safety. Current methods, such as Maximum Power Checks (MPCs), are effective but resource-intensive and infrequent. This paper presents...
The combination of servitization and digitalization is increasingly changing the economy and society at the global level towards sustainability goals. Companies are shifting their business models, typically oriented to selling products, towards provi...
Antimicrobial resistance and biofilm-associated contamination continue to pose critical challenges in food safety and biomedical applications, necessitating the development of advanced antimicrobial materials with enhanced efficacy, safety, and funct...
For highly maneuverable aircraft, the afterburning engine serves as a core and critical component. Due to the complex structure of the afterburner and the strong coupling among parameters, mechanism-based modeling of afterburning engines remains extr...
This paper presents a data-driven educational framework for teaching psychrometry and air quality control in hospitals, developed within an international pilot project involving universities and hospitals in Spain, Romania, and Turkey. The objective...
Component degradation in aero-engines can cause local model mismatch. Insufficient coordination between component-response updates and engine-level prediction correction may limit improvements in gas-path prediction accuracy. Therefore, a data-enhanc...
Despite advances in digital engineering tools, early-stage sheet metal forming tooling design remains strongly dependent on the tacit knowledge of experienced engineers, making systematic knowledge reuse difficult. This study addresses the need for a...
Adaptive control of traffic engineering (TE) based on 5G network function virtualization (NFV) authorizes the efficient and dynamic network resource allocation, whose utilization is increasingly wide and will become more widespread. In this paper, we...
Artificial neural networks (ANNs) are widely used to approximate nonlinear mappings, yet their ability to capture thermodynamic behaviour in dynamic physical systems remains insufficiently characterised. This study investigates how representational c...
In order to reduce pollutants of the emission from diesel vehicles, complex after-treatment technologies have been proposed, which make the fault detection of diesel engines become increasingly difficult. Thus, this paper proposes a canonical correla...
Fault detection in marine diesel engine lubrication systems is crucial for ensuring the long-term stable operation of diesel engines and the safety of maritime navigation. Traditional fixed-parameter alarm threshold methods lack flexibility and are p...
Process re-engineering and optimization in manufacturing industries is a big challenge because of process interdependencies characterized by a high failure rate. Research has shown that over 70% of approaches fail because of complexity as a result of...
Aiming at the problems of the large prediction error of model-driven algorithms and poor interpretability (even potential violation of physical laws) of pure data-driven algorithms in the prediction of aerospace vehicle plume characteristics, a physi...
As modern marine diesel engine systems become increasingly complex, effective condition monitoring methods are essential for ensuring optimal performance and preventing anomalies. This paper proposes a data-driven condition monitoring approach specif...
This study explores the fabrication and characterisation of 3D-printed polylactic acid (PLA) scaffolds reinforced with calcium hydroxyapatite (cHAP) for bone tissue engineering applications. By varying the cHAP content, we aimed to enhance PLA scaffo...
Accessible restrooms must reconcile code-based functionality with the affective expectations of disabled users. This study develops an integrated Kansei Engineering (KE)–Rough Set Theory (RST)–Support Vector Machine (SVM) workflow that co...
The digital transformation of manufacturing enterprises necessitates more efficient engineering change management through data-driven decision support and process optimization. Although process mining has advanced considerably in recent years, most e...
In the last few decades, structural health monitoring has gained relevance in the context of civil engineering, and much effort has been made to automate the process of data acquisition and analysis through the use of data-driven methods. Currently,...
(1) Background: “Kidney Disease: Improving Global Outcomes” (KDIGO) provides guidelines for identifying the stages of acute kidney injury (AKI) and chronic kidney disease (CKD). A data-driven rule-based engine was developed to determine K...
Transmembrane pressure (TMP) is a central state variable in haemodialysis (HD) and haemodiafiltration (HDF), governing ultrafiltration dynamics, convective transport, and membrane performance. Although dialysis devices specify high maximum allowable...
This study presents a data-driven and explainable artificial intelligence (XAI) framework for quantitatively analyzing research trends in the seismic performance of timber structures. Unlike conventional bibliometric approaches based on descriptive s...
Accurate estimation of the State of Charge (SOC) for lithium-ion batteries is a core function of the Battery Management System (BMS). However, LiFePO4 batteries present specific challenges for SOC estimation due to the characteristic plateau in their...
X-ray powder diffraction (XRPD) occupies a central place in the structural characterization toolbox of materials engineering, providing phase identification, lattice-parameter determination, and microstructural information within a single analytical...
To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing...
Climate change, soil degradation, and the disruption of global nutrient cycles are placing unprecedented pressure on agricultural systems and global food security. These challenges are increasingly recognized as central concerns for planetary health,...
Artificial Intelligence (AI) can change how automotive engines are maintained and monitored in the future. This paper presents an Adaboost-based model to monitor engine health with real-world data. Key engine metrics such as temperature, pressure, an...
Over the last two decades, there has been a paradigm shift in geotechnical engineering driven by advances in sensing, communication, and data-driven techniques. These advancements enhanced the safety and reliability of geotechnical infrastructure thr...
This special issue aims at exploring advanced numerical techniques for real-time prediction and optimal management in coastal and hydraulic engineering [...]
To enable proactive prediction of marine diesel engine failure time and root causes, thereby reserving sufficient time for maintenance, this study proposes a data-driven multi-algorithm integration framework for performance assessment and fault early...
Object tracking is an essential problem in computer vision that has been extensively researched for decades. Tracking objects in thermal images is particularly difficult because of the lack of color information, low image resolution, or high similari...
Remote sensing products are typically assessed using a single accuracy estimate for the entire map, despite significant variations in accuracy across different map areas or classes. Estimating per-pixel uncertainty is a major challenge for enhancing...
The electric power industry poses significant risks to workers with a wide range of hazards such as electrocution, electric shock, burns, and falls. Regardless of the types and characteristics of these hazards, electric power companies should protect...
The use of biodiesel blends in heavy-duty diesel engines changes the relationship between engine operating conditions, fuel properties, and exhaust emissions, which may limit the reliability of data-driven emission models trained under a single fuel...
The increasing volume of data from IoT sensors has made manual inspection time-consuming and prone to bias, particularly for spatiotemporal air pollution maps. While rule-based methods are adequate for simple datasets or individual maps, they are ins...
Offshore engineering microgrids integrate renewable generation, energy storage, and large marine test loads. Frequent start-stop transients of test loads, strong wind/PV fluctuations, and saline–humid conditions accelerate equipment aging and t...
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