Systems Engineering Research Articles

Alternating Donor‐Acceptor Ladder‐Type Heteroarene for Efficient Photothermal Conversion via Boosting Non‐Radiative Decay

The development of novel ladder‐type conjugated molecules is crucial for advancing supramolecular chemistry and material science. In this study, we report a straightforward synthesis of new alternating donor‐acceptor (D‐A) ladder‐type heteroarene, FCDTDPP, and demonstrate its application as photothermal agent for imaging and cancer therapy. FCDTDPP is constructed by vinylene bridge between cyclopentadithiophene (D) and diketopyrrolopyrrole (A) through intramolecular Friedel‐Crafts type reaction. FCDTDPP exhibits unique combination of good molecular planarity, efficient intra/inter‐molecular mixed D‐A interactions, and local aromaticity. These features collectively contribute to its broad and intense absorptions with narrow bandgap in red band of the spectra, coupled with multiple vibrational absorption feature, thereby enhancing non‐radiative decay process and resulting in efficient photothermal conversion property. FCDTDPP and its nanoparticles (NPs) exhibit superior photothermal conversion performance and stability under 660 nm laser irradiation. Moreover, in vitro studies reveal that FCDTDPP NPs possess excellent biocompatibility, low cytotoxicity, and robust photothermal therapeutic efficacy, a finding further corroborated by preliminary in vivo experiments in tumor‐bearing mice. This work charts a novel course for the molecular engineering of organic photothermal conversion systems, propelling relevant research forward.

Alternating Donor‐Acceptor Ladder‐Type Heteroarene for Efficient Photothermal Conversion via Boosting Non‐Radiative Decay

The development of novel ladder‐type conjugated molecules is crucial for advancing supramolecular chemistry and material science. In this study, we report a straightforward synthesis of new alternating donor‐acceptor (D‐A) ladder‐type heteroarene, FCDTDPP, and demonstrate its application as photothermal agent for imaging and cancer therapy. FCDTDPP is constructed by vinylene bridge between cyclopentadithiophene (D) and diketopyrrolopyrrole (A) through intramolecular Friedel‐Crafts type reaction. FCDTDPP exhibits unique combination of good molecular planarity, efficient intra/inter‐molecular mixed D‐A interactions, and local aromaticity. These features collectively contribute to its broad and intense absorptions with narrow bandgap in red band of the spectra, coupled with multiple vibrational absorption feature, thereby enhancing non‐radiative decay process and resulting in efficient photothermal conversion property. FCDTDPP and its nanoparticles (NPs) exhibit superior photothermal conversion performance and stability under 660 nm laser irradiation. Moreover, in vitro studies reveal that FCDTDPP NPs possess excellent biocompatibility, low cytotoxicity, and robust photothermal therapeutic efficacy, a finding further corroborated by preliminary in vivo experiments in tumor‐bearing mice. This work charts a novel course for the molecular engineering of organic photothermal conversion systems, propelling relevant research forward.

STL4IoT: a statechart template library for IoT system design

The engineering of IoT systems brings about various challenges due to the inherent complexities associated with such heterogeneous systems. In this paper, we propose a library of statechart templates, STL4IoT, for designing complex IoT systems. We have developed atomic statechart components modeling the heterogeneous aspects of IoT systems including sensors, actuators, physical entities, network, and controller. Base system units for smart systems have also been designed. A component for calculating power usage is available in the library. In addition, a smart hub template that controls interactions among multiple IoT systems and manages power consumption has also been proposed. The templates aim to facilitate the modeling and simulation of IoT systems. Our work is demonstrated with a smart home system consisting of a smart hub of lights, a smart microwave, a smart TV, and a smart fire alarm system. We have created a multi statechart with Itemis CREATE based on the proposed templates and components. A smart home simulator has been developed by generating controller code from the statechart and integrating it with a user interface.

Modeling Borehole Resistivity Logs with Exponentially Graded Multilayered Soil Inversion for Electrical Engineering Applications

In this paper, we present the application of a special soil resistivity model, the Exponentially Graded Multilayered Soil model, to the interpretation of Borehole Resistivity Logging surveys. The model, which was recently introduced by the authors, offers an alternative to the interpretation provided by constant resistivity layer models. The model is applied to synthetic soil surveys as well as to a real survey that is not satisfactorily interpreted using conventional models. This model aids in the design and calculation of grounding systems in electrical engineering, providing an alternative to calculations performed by traditional layered models.

Real-time in-situ ultrasound monitoring of soft hydrogel 3D printing with subwavelength resolution

3D bioprinting has excellent potential in tissue engineering, regenerative medicine, and drug delivery systems due to the ability to fabricate intricate structures that are challenging to make with conventional manufacturing methods. However, the complexity of parametric combinations and lack of product quality control have restricted soft hydrogel bioprinting from practical applications. Here we show an in-situ ultrasound monitoring system that reveals the alginate-gelatin hydrogel’s additive manufacturing process. We use this technique to understand the parameters that influenced transient printing behaviors and material properties in approximately real-time. This unique monitoring process can facilitate the detection of minor errors/flaws during the printing. By analyzing the ultrasonic reflected signals in both time and frequency domains, transient printing information can be obtained from 3D printed soft hydrogels during the processes with a depth subwavelength resolution approaching 0.78λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}. This in-situ technique monitors the printing behaviors regarding the constructed film, interlayer bonding, transient effective elastic constant, layer-wise surface roughness (elastic or plastic), nozzle indentation/scratching, and gravitational spreading. The simulation-verified experimental methods monitored fully infilled printing and gridded pattern printing conditions. Furthermore, the proposed ultrasound system also experimentally monitored the post-crosslinking process of alginate-gelatin hydrogel in CaCl2 solution. The results can optimize crosslinking time by balancing the hydrogel’s stiffness enhancement and geometrical distortion.

Human Factors Engineering (HFE) Considerations for Mounting Internal Interfaces in Heavy Vehicles

Trucking fleets often need to install additional displays and consoles in vehicles to interface with the driver. These devices may be used for fleet management, assistance with logistics, or connecting to business applications. However, if these devices are installed without consideration of the drivers, the users may become distracted or frustrated with the system. Therefore, a human factors engineering (HFE) approach to the installation of additional console(s) reduces the likelihood of rework, distractions, and driver inconvenience. Model-based systems engineering (MBSE) approach utilizing best practices for HFE design is presented in this paper. The results of the effort are captured with a prototype assembly bracket used in the production version of the heavy vehicle. The plan-do-study-act (PDSA) model-based human factors systems engineering methodology demonstrates efficiencies in the design and implementation of the display system. This method proved effective as new mounts were fitted in a preproduction electric vehicle before they were released in production.

Bayesian optimization for state engineering of quantum gases

Abstract State engineering of quantum objects is a central requirement for precision sensing and quantum computing implementations. When the quantum dynamics can be described by analytical solutions or simple approximation models, optimal state preparation protocols have been theoretically proposed and experimentally realized. For more complex systems such as interacting quantum gases, simplifying assumptions do not apply anymore and the optimization techniques become computationally impractical. Here, we propose Bayesian optimization based on multi-output Gaussian processes to learn the physical properties of a Bose-Einstein condensate within few simulations only. We evaluate its performance on an optimization study case of diabatically transporting the quantum gas while keeping it in its ground state. Within a few hundred executions, we reach a competitive performance to other protocols. While restricting this benchmark to the well known Thomas-Fermi approximation for straightforward comparisons, we expect a similar performance when employing more complex theoretical models, which would be computationally more challenging, rendering standard optimal control theory protocols impractical. This paves the way for efficient state engineering of complex quantum systems including mixtures of interacting gases or cold molecules.

Characteristics of pollutants emitted by motor vehicles and their impact on the environment and engine operation

Gaseous and solid pollutants (dusts) of atmospheric air have been defined. Dusts have been divided according to various criteria and their properties have been given. The sources and characteristics of anthropogenic and natural pollutants of atmospheric air have been presented. It has been shown that the main sources of anthropogenic pollutants, apart from industry, are motorization, and internal combustion engines of cars are a source of gaseous pollutants and solid particles, the emission of which has been significantly reduced. The originality of the article consists in conducting an extensive literature analysis and proving that the emission of "non-engine" pollutants in the form of dust from the wear of friction linings of brakes, clutches and from the wear of tires and roads, as well as mineral dust raised from the ground, is currently a greater threat to human health and the environment than engine emissions. The impact of particulate matter emissions from road transport and mineral dust, which is the basic component of road dust, on human health, vegetation and on the operation of engine and vehicle systems is presented.

Dynamic reliability measures of weighted k-out-of-n system with heterogeneous components and its application to solar power generating system

In the realm of dynamic reliability analysis, this research paper presents a novel mathematical model for the weighted k-out-of- n system with two heterogeneous components also said to be weighted ( k1, k2)-out-of- n repairable system. This innovative framework comprises two distinct component types, whose simultaneous functioning yields system operation if and only if the cumulative weight of the operational type 1 component is at least k1, and that of the type 2 component is at least, k2. Each component type has a number of distinct individual components with variable states that change over time, making the state probabilities of those components time-dependent. By employing an algorithm grounded in L z-transform, dynamic reliability measures comprising reliability, availability, mean expected performance, and expected profit are derived for the system taken into consideration. This study also introduces a pioneering connection between the L z-transform and queueing theory and extends its implications to various intricate engineering systems meeting the established criteria.

Critical Role of Solenoid Valves in Modern Engine Design

Solenoid valves, which serve as actuators, are vital in engine design because they can precisely control fluid and gas flow within the engine systems. This allows fuel injection, emission controls, and better performance in modern engines. This paper explores the role that a solenoid valve has been playing in engine designs and underlines its importance for fuel efficiency, emission reduction, and reliability of the engine's performance. Keywords—Solenoid valves, Actuators, Engine control, Fuel injection, Emission control, Engine performance, Valve timing, Fluid flow regulation, Engine Braking, Piston cooling Nozzle valve, CAM phaser Control.

Overview on Current Selectable Marker Systems and Novel Marker Free Approaches in Fruit Tree Genetic Engineering

Selectable marker genes are useful for recognizing which cells have integrated specific sequences in their genome after genetic transformation processes. They are especially important for fruit trees genetic transformation to individuate putatively genetically modified events, because most of the protocols used to genetic engineer these species are often unsuccessful or with low efficiency. Traditional selectable marker genes, mainly of bacterial origin, confer antibiotics/herbicides-resistance or metabolic advantages to transformed cells. Genes that allow the visual recognition of engineered tissues without using any selective agent, such as morphogenic regulators and reporter genes, are also used as selection tools to in vitro identify genetically modified regenerated lines. As final step, genetic engineered plants should be tested in field conditions, where selectable marker genes are no longer necessary, and strongly unpopular especially for the commercial development of the new products. Thus, different approaches, mainly based on the use of site-specific recombinases and/or editing nucleases, are being now used to recover marker-free fruit crops. This review describes and comments the most used and suitable selection tools of interest, particularly for fruit tree genetic engineering. Lastly, a spotlight highlights the biosafety aspects related to the use of selectable marker genes exploited for fruit species genetic engineering.

Intelligent Helicopter Turbine Engine Fault Diagnosis Using Multi-Head Attention

A turbine engine provides power to the helicopter, enabling the helicopter to travel and hover in the air. Since the rotorcraft operates at high altitudes, ensuring safety and maintaining a healthy operational status are crucial at all times. Therefore, a prognostics and health management (PHM) system for the turbine engine must be implemented to predict any anomalies or faults to prevent catastrophic accidents. This research proposes a novel fault diagnosis method for helicopter turbine engines based on operational data acquired from actual aircraft. First, the proposed method predicts engine torque using other operational data while accounting for uncertainty. A Bayesian regression approach is employed to predict the engine torque. The torque margin, defined as the difference between the actual torque and the estimated torque, is then used to diagnose engine faults. Specifically, a multi-head attention mechanism is incorporated to capture interactions between various engine parameters. Additionally, domain adaptation techniques are applied to enhance the model's generalization performance, ensuring robustness across diverse operating conditions. The proposed method is validated using seven different datasets, each acquired from a helicopter engine. Four datasets were used for training, while the remaining three were allocated for testing and validation. The results indicated that the proposed method accurately predicted torque. Furthermore, the fault diagnosis showed promising results, leading to a 3rd-place finish in the 2024 PHM Society Data Challenge in terms of validation score.

Artificial intelligence and machine learning at various stages and scales of process systems engineering

AbstractWe review the utility and application of artificial intelligence (AI) and machine learning (ML) at various process scales in this work, from molecules and reactions to materials to processes, plants, and supply chains; furthermore, we highlight whether the application is at the design or operational stage of the process. In particular, we focus on the distinct representational frameworks employed at the various scales and the physics (equivariance, additivity, injectivity, connectivity, hierarchy, and heterogeneity) they capture. We also review AI techniques and frameworks important in process systems, including hybrid AI modelling, human‐AI collaborations, and generative AI techniques. In hybrid AI models, we emphasize the importance of hyperparameter tuning, especially in the case of physics‐informed regularization. We highlight the importance of studying human‐AI interactions, especially in the context of automation, and distinguish the features of human‐complements‐AI systems from those of AI‐complements‐human systems. Of particular importance in the AI‐complements‐human framework are model explanations, including rule‐based explanation, explanation‐by‐example, explanation‐by‐simplification, visualization, and feature relevance. Generative AI methods are becoming increasingly relevant in process systems engineering, especially in contexts that do not belong to ‘big data’, primarily due to the lack of high quality labelled data. We highlight the use of generative AI methods including generative adversarial networks, graph neural networks, and large language models/transformers along with non‐traditional process data (images, audio, and text).

Non-invasive, continuous oral delivery of solid levodopa-carbidopa for management of Parkinson's disease.

When short plasma half-life drugs act only briefly, they require frequent or continuous administration. We report the engineering of a non-invasive oral drug delivery system for long-term, continuous administration of these drugs. Their non-invasive, long-term, continuous administration at daily doses exceeding 100 mg has, for many years, been considered an insurmountable challenge. We show that over 1200 mg/day of 4:1 levodopa-carbidopa (LD-CD) can be non-invasively and continuously extruded when formulated as a semisolid paste, loaded with 63%w/w of the solid drugs. The drug delivery system comprises a reusable orthodontic retainer with a co-molded pocket into which the patient inserts after each meal a new 1 mL propellant-driven, prefilled, disposable, drug delivery extruder. The paste is delivered to the lingual side of the teeth where it is mixed with saliva and swallowed. As reported elsewhere, a 15-day, 16 patient open label clinical trial of the drug delivery system continuously extruding LD-CD paste significantly reduces the variability of the plasma LD concentration and alleviates symptoms of advanced Parkinson's disease (PD) as compared to LD-CD tablets.

Torsional damper design for diesel engine: theory and application

Abstract Torsional vibration is the primary cause of engine crankshaft failure. Consequently, the reduction of engine vibration is of paramount importance for the enhancement of automotive safety and comfort. However, the lack of comprehensive insight into the damping mechanism of the torsional damper has impeded the effective control of engine torsional vibration. In order to gain insight into the vibration characteristics of the shaft system in an inline six-cylinder diesel engine, an analysis of the system’s behaviour during both free and forced vibration was conducted. A mathematical relationship was deduced between the dimensions, material, operational temperature and damping properties of the silicone oil damper. The objective was to determine the optimal damping and moment of inertia of the damper, with the aim of minimizing the torsional amplitude of the sixth harmonic. The results demonstrate a reduction in the six-harmonic torsional amplitude from 0.32° to 0.14° following the installation of the damper. The mean and relative deviations between the calculated and experimental results are 0.0018° and 0.83%, respectively. To facilitate the design of the silicone oil damper, a software program, Vibsim, was developed based on Visual Studio for the design and torsional vibration analysis of the silicone oil damper. This software is reliable in calculating results and is user-friendly.

Mission Design and Validation of a Fixed-Wing Unmanned Aerial Vehicle for Environmental Monitoring

Climate change is becoming a worldwide emergency. In order to prevent catastrophic levels of climate change, three broad categories of action are ongoing: cutting emissions, adapting to climate impacts, and financing required adjustments. Cutting emissions requires stopping the use of fossil fuels in favor of renewable energy sources. Adapting to climate change and financing required adjustments need instruments for the understanding of the source causes and how effective the potential measures are. In this context, the use of Unmanned Aerial Vehicles for environmental monitoring is continuously increasing thanks to their ability to collect a wide range of environmental data, from the quality of air to the health status of vegetation, waters, and lands. This paper describes the research activities that are being performed for the design and development of a 100 kg Max Take Off Mass prototype zero-emission Unmanned Aerial Vehicle, named Daphne, destined for environmental monitoring, surveillance, and inspection missions. The developed prototype will drive the next industrialization of the vehicle. A particular focus is given to the design of the power system, based on the use of Proton Exchange Membrane fuel cells fueled with green hydrogen, the integration of the sensors allowing for multipurpose observations and measurements, and the design and validation of the relative multi-purpose missions via an innovative approach based on Model-Based System Engineering.

Hybrid genetic algorithm with Wiener process for multi-scale colored balanced traveling salesman problem

Colored traveling salesman problem (CTSP) can be applied to Multi-machine Engineering Systems (MES) in industry, colored balanced traveling salesman problem (CBTSP) is a variant of CTSP, which can be used to model the optimization problems with partially overlapped workspace such as the planning optimization (For example, process planning, assembly planning, productions scheduling). The traditional algorithms have been used to solve CBTSP, however, they are limited both in solution quality and solving speed, and the scale of CBTSP is also restricted. Moreover, the traditional algorithms still have the problems such as lacking theoretical support of mathematical physics. In order to improve these, this paper proposes a novel hybrid genetic algorithm (NHGA) based on Wiener process (ITÖ process) and generating neighborhood solution (GNS) to solve multi-scale CBTSP problem. NHGA firstly uses dual-chromosome coding to construct the solutions of CBTSP, then they are updated by the crossover operator, mutation operator and GNS. The crossover length of the crossover operator and the city number of the mutation operator are controlled by activity intensity based on ITÖ process, while the city keeping probability of GNS can be learned or obtained by Wiener process. The experiments show that NHGA can demonstrate an improvement over the state-of-art algorithms for multi-scale CBTSP in term of solution quality.

Multi-objective optimization of vibrating particle systems applied to engineering system design

Multi-objective optimization of vibrating particle systems applied to engineering system design

Increasing accuracy in predicting mode I fracture toughness of rock structures: a comparative analysis of the rock engineering system method

The investigation of crack initiation and expansion is vital for the stability of structures. The Mode I fracture toughness (KIc) of rocks is a key property used to predict crack propagation in tension and hydraulic fracturing. Various methods have been introduced to determine KIc, but results differ due to factors like sample dimensions, crack geometry, groove type, and loading conditions. The cracked chevron notched Brazilian disc (CCNBD) sample is commonly used in laboratory tests for its easy preparation. This study employs the rock engineering system (RES) technique to overcome the challenges of time-consuming and costly laboratory tests and the uncertainty in traditional methods (analytical, numerical, experimental, laboratory, regression). Using 88 CCNBD rock samples proposed by ISRM, input parameters include thickness of the disc specimen (B), uniaxial tensile strength (σt), initial crack length (α0), radius of the disc specimen (R), crack length (αB), and the length of the final crack (α1). The RES-based model used 70 data points (80% of the dataset) for development, and 18 data points (20%) for evaluation. Regression analysis compared the performance of the RES method, using statistical indicators such as squared correlation coefficient (R2), mean square error (MSE), and root mean square error (RMSE) to measure accuracy. The RES-based method outperformed other regression techniques, demonstrating significantly enhanced accuracy. This highlights the effectiveness and superior performance of the RES method in estimating fracture toughness, particularly for CCNBD samples, showcasing its potential as a robust analytical tool.

SH‐waves in a complex fluid composite structure with spring membrane imperfect interfaces

AbstractComplex fluids are of nobleness due to their unique mechanical responses to applied stress, which are different from simple fluids. Therefore, the current study encapsulated the behavior of SH‐wave in a complex fluid layer overlying a fiber‐reinforced half‐space with six different cases considered at the common interface. These cases involve various interface conditions, including perfect bonding, a spring layer, an infinitely thin membrane layer, loose bonding, a combined spring‐membrane layer, and a membrane layer with loose bonding. Precisely, the effect of loose bonding, membrane strength, and spring stiffness at the common interface on the propagation of SH (Shear Horizontal) wave is studied in detail. The problem is mathematically formulated for all the aforementioned six models followed by their solution with the aid of appropriate boundary conditions. Numerical computations are performed with a view to study the effect of stiffness of spring and membrane, as well as loose bonding at the common interface of the media. It is demonstrated that membrane strength impedes wave propagation, while increased spring stiffness supports it. Notably, the combined spring‐membrane interface has a more pronounced effect than a spring layer alone. The findings of this study may be utilized in the development of membrane technology, including the study of fluid membranes and it has significant importance in seismic engineering and vibration isolation systems.