Systems Engineering Research Articles

CFD Simulation of Pre-Chamber Spark-Ignition Engines—A Perspective Review

The growing demand to reduce emissions of pollutants and CO2 from internal combustion engines has led to a critical need for the development of ultra-lean burn engines that can maintain combustion stability while mitigating the risk of knock. One of the most effective techniques is the pre-chamber spark-ignition (PCSI) system, where the primary combustion within the cylinder is initiated by high-energy reactive gas jets generated by pilot combustion in the pre-chamber. Due to the complex physical and chemical processes involved in PCSI systems, performing 3D CFD simulations is crucial for in-depth analysis and achieving optimal design parameters. Moreover, combining a detailed CFDs model with a calibrated 0D/1D model is expected to provide a wealth of new insights that are difficult to gather through experimental methods alone, making it an indispensable tool for improving the understanding and optimization of these advanced engine systems. In this context, numerous previous studies have utilized CFD models to optimize key design parameters, including the geometric configuration of the pre-chamber, and to study combustion characteristics under various operating conditions in PCSI engines. Recent studies indicate that several advanced models designed for conventional spark-ignition (SI) engines may not accurately predict performance under the demanding conditions of Turbulent Jet Ignition (TJI) systems, particularly when operating in lean mixtures and environments with strong turbulence–chemistry interactions. This review highlights the pivotal role of Computational Fluid Dynamics (CFDs) in optimizing the design of pre-chamber spark-ignition (PCSI) engines. It explores key case studies and examines both the advantages and challenges of utilizing CFDs, not only as a predictive tool but also as a critical component in the design process for improving PCSI engine performance.

Preparation and study on electrical/thermal properties of epoxy/polyacrylate rubber composite dielectric

AbstractWith the development of power systems and electronic devices, epoxy resin (EP) is facing increasingly severe operating environments, and its performance may not meet expectations. In order to broaden the application of EP, the DE/EP composite films were prepared with EP as matrix, polyacrylic rubber dielectric elastomer (DE) as reinforcement materials. The structure of DE/EP composite films was characterized by XRD, SEM, and other methods, and the electrical and thermal properties of the materials were tested and studied. The study found that with appropriate dissolution and stirring treatment, DE can be evenly dispersed in the EP matrix, and the introduction of DE does not significantly affect the structure of the EP molecular chain, also found the introduction of DE improve the electrical and thermal properties of EP. The breakdown strength of the 4% DE/EP composite film surpasses that of the pure EP film by 15.58%. Additionally, the thermal conductivity of the 8% DE/EP composite film is elevated by 41.6% compared to the pure EP film, while its dielectric constant is also enhanced by 8.2%. This work may provide a theoretical basis for studying the application of EP modified system in electrical engineering, integrated circuit packaging and other fields.

A Novel Stock Price Prediction and Trading Methodology Based on Active Learning Surrogated with CycleGAN and Deep Learning and System Engineering Integration: A Case Study on TSMC Stock Data

Technical analysis, reliant on statistics and charting tools, is a predominant method for predicting stock prices. However, given the impact of the joint effect of stock price and trading volume, analyses focusing solely on single factors at isolated time points often yield partial or inaccurate results. This study introduces the application of Cycle Generative Adversarial Network (CycleGAN) alongside Deep Learning (DL) models, such as Residual Neural Network (ResNet) and Long Short-Term Memory (LSTM), to assess the joint effects of stock price and trading volume on prediction accuracy. By incorporating these models into system engineering (SE), the research aims to decode short-term stock market trends and improve investment decisions through the integration of predicted stock prices with Bollinger Bands. Thereby, active learning (AL) is employed to avoid over-and under-fitting and find the hyperparameters for the overall system model. Focusing on TSMC’s stock price prediction, the use of CycleGAN for analyzing 30-day stock data showcases the capability of ResNet and LSTM models in achieving high accuracy and F-1 scores for a five-day prediction period. Further analysis reveals that combining DL predictions with SE principles leads to more precise short-term forecasts. Additionally, integrating these predictions with Bollinger Bands demonstrates a decrease in trading frequency and a significant 30% increase in average Return on Investment (ROI). This innovative approach marks a first in the field of stock market prediction, offering a comprehensive framework for enhancing predictive accuracy and investment outcomes.

Manipulating conductivity and noise for transitioning between stochastic and inverse stochastic resonances in liquid–crystal electroconvection

Noise can play a constructive role in nature and various engineering systems. Over the past four decades, noise-induced stochastic resonances (SRs) have been extensively documented, showing enhancement in system performance. Additionally, inverse SR has been observed in various systems. Typically, these resonances were studied independently. A transition between these resonances was recently observed in an alternating current-driven liquid–crystal electroconvection (EC) system using combined amplitude and phase noises. This study uses internal (material) and external (noise) parameters to demonstrate the control of this transition. Specifically, the nonmonotonic threshold voltage behavior of the EC system, indicative of the resonances, was numerically examined using additional parameters. Experimental tests were conducted to confirm the effects of these parameters. The findings reveal that the transition between these resonances can be systematically controlled to meet specific needs, whether desirable or undesirable system performances. Notably, this study illustrates how to modify the behavior of both resonances in colored noise by adjusting its cutoff frequency and steepness and phase noise, which is often overlooked. Moreover, this study provides valuable insights for various noise-related applications.

Early Design Stage Evaluation of All Electric Aircraft Power Systems Focusing on Long-Term Behavior

In the aircraft industry, there is a shift towards more and all-electric power systems resulting in great research efforts on single components like batteries. At the same time there is an increasing need to investigate and evaluate the long-term behavior of the whole electric power system to ensure safe and sustainable aircraft operation. Focusing on this challenge, the objective of this article is to propose a framework for electric power system assessment in the early design stages. In particular, the focus is on identifying and handling uncertainties regarding failure behavior and degradation, both on the component and system level. The evaluation of different power system topologies is based on the integration of Model-Based Systems Engineering and robust design methods. In this context, another central aspect is the definition of system and component requirements derived from the flight mission profile. SysML diagrams are used to define use cases and possible system topologies. Sensitivity of degradation effects are evaluated using robust design methods. The application of the framework and these methods is illustrated using a short-range aircraft with an all-electric power system. The results highlight the applicability of the framework to cope with the uncertainties that occur in the early design stages and point out fields of further research.

The dynamic behaviour of a finite periodic structure comprising either symmetric or asymmetric exponential- and conical-shaped rods

Periodic structure research is driven by the aim of incorporating them into modern engineering systems to address specific challenges, such as vibration reduction within defined frequency ranges. This paper explores the dynamic behaviour of a periodic structure comprising rods with varying cross-sectional areas. Two specific cases are considered, one in which the unit cell consists of two rods where the cross-sectional area varies exponentially and one where the cross-sectional areas vary conically. The structures are modelled using receptance matrices of a single cell, which are then transformed into transfer matrices. This facilitates a comparison of the two structures and helps to relate the results between finite and infinite structures. An experimental study to validate the approach and some of the results is also presented. It is shown that the structures composed of rods with exponentially or conically varying cross-section areas have similar behaviour. Reasonably good correspondence between the predictions and the experimental results were found. However, some additional features were found in the measured receptances due to bending vibration that was not considered in the theoretical model. Asymmetric cells are found to perform better and have a wider attenuation band when compared to symmetrical cells.

Solvent Vapor/Gas-Induced Guest Transport and Exchange of a Nonporous Organic Crystal to Construct Smart Host-Guest Energetic Materials.

Supramolecular materials with advanced properties constructed by intermolecular interactions have attracted extensive attention in many fields, such as sensing, catalysis, and biomedicine. However, in the field of energetic materials, limited by the tight-packed crystal structure of explosives and the strong intermolecular interaction forces, most supramolecular explosives can only be obtained in organic solution or under extreme external loading (high temperature/high pressure). Given the practical issues such as safety risks, operational difficulties, serious environmental pollution, and large-scale production of the existing technology, a new method of constructing host-guest explosives by solvent vapor/gas induction is proposed. This gas-solid reaction method takes advantage of the metastable properties from the explosives solvate (HNIW/ACN), and cleverly opens a fast channel for gas molecules to enter the explosives cell cavities, which results in the highly efficient preparation of the host-guest explosives (HNIW/CO2 and HNIW/N2O). The embedding of functional gas molecules greatly improves the structural stability and comprehensive performance of the explosive skeleton, and the detonation velocity of HNIW/N2O even reaches 9802 m·s-1, which is higher than that of ε-HNIW (9455 m·s-1). In addition, compared with ε-HNIW, HNIW/CO2 and HNIW/N2O exhibit high energy but low sensitivity, enhanced thermal stability, and combustion properties, which present a potential prospect in the field of energetic materials. The new method effectively overcomes the high-energy barrier of nonporous organic explosives, offering the advantages of simplicity, safety, efficiency, and environmental friendliness. This study provides a valuable pathway for constructing advanced supramolecular energetic materials, which contributes to the enrichment of supramolecular engineering systems.

A grouping module assessment method for ocean engineering systems: Subsea tree system as a case

In the ocean engineering environment, the quality failure data of complex systems are difficult to obtain due to the high experiment cost. In addition, using a single model to analyze risk, reliability, availability, and maintainability is a big challenge. Based on the fault tree, Dynamic Bayes and Markov models, a state assessment method for ocean engineering systems with multiple maintenance modes is proposed in this paper. This method gives full play to the advantages of the three methods, and comprehensively analyzes the risk, reliability, availability and maintainability. This method uses fault tree and Markov model to pre-process fault data, and then inputs the pre-processed fault data into the multi-state degradation model based on dynamic Bayesian theory. Considering the maintenance strategies of no repair, perfect repair, imperfect repair and preventive repair, the model is iterated and adjusted until the model has processed all the event data and the updated model can best reflect the state of the system. The method is verified by taking the subsea tree of the subsea production system as an example. The obtained tree reliability index (mean time without failure) is basically consistent with the failure statistics of offshore and onshore reliability databases, which verifies the accuracy of the proposed method.

Influence of gamma radiation on the composition and physicochemical characteristics of olefins: post-radiation effects

The effect of gamma radiation on olefins was studied under static conditions at an absorbed dose of 65 kGy and at a dose rate ofP= 0.076 Gy/s. The effect of radiation on the physicochemical characteristics and structural and group composition of the resulting olefins has been established. Post-irradiation effects were studied immediately after irradiation and during 1, 2, 4, and 7 months later. When fuels are irradiated, polymerization of unsaturated hydrocarbons occurs. After cessation of irradiation, the postpolymerization process occurs The chemical instability of olefins in fuels leads to the formation of carbon deposits in the engine system, tanks, and valves. IR spectra, iodine values, density, and kinematic viscosity of irradiated samples were measured.

Enhancing operational performance assessment of structures with seismic response modification devices: The role of observability and symmetry analysis under limited sensor deployment

AbstractTo manage structural responses under various external forces, the increasing incorporation of seismic isolation and supplementary damping systems in modern civil engineering necessitates post‐installation performance assessments. The challenge of accurately inferring system information from these complex dynamical structures, especially with limited sensor deployment, could be significant. From the perspective of solving inverse problems, this challenge hinges on constructing an input‐output mapping that assures unique solutions, achievable through theoretical observability or symmetry analysis. We introduce a unified algorithm framework designed to accommodate various definitions of Lie derivatives, specifically for observability and symmetry analysis in dynamic systems with affine, non‐affine, and unknown inputs—capabilities not fully achieved in previous studies. We demonstrate its application across typical dynamic scenarios, including both linear and nonlinear examples. We also present a numerical example featuring complex isolation systems with limited sensor layouts, illustrating how uniform convergence can be achieved in estimating all system states when an observable input‐output mapping is utilized. Furthermore, an experimental example employing shaking table tests showcases the potential complications that arise when an unobservable input‐output mapping is used.

Research on information extension of mountainous rack railway engineering based on IFC standard

In response to the practical demands for data sharing and exchange in the field of rack railway systems engineering, as well as to address the gaps in the rack railway domain within the framework of the IFC4 standard, we extend and define the rack railway domain through entity extension and custom attribute sets. By utilizing the ongoing construction of the Dujiangyan to Mount Siguniang Railway as a case study, we validate the utility of this IFC extension and modeling approach. Leveraging IfcOpenShell, we incorporate the extended data content into the generated IFC file. We present a process for extension tailored to the characteristics of rack railway engineering. This study aims to provide broader information support for the digital construction of track structures in the design phase of rack railway engineering and to facilitate more efficient data exchange and sharing.

Preliminary Design of Satellite Systems through the Integration of Model-Based System Engineering and Agile Methodologies: Application to the 3ColStar Mission

This paper presents a case study on integrating Agile Systems Engineering methodologies in the preliminary design phase of satellite systems, focusing on the 3ColStar satellite mission. Through Model-Based Systems Engineering (MBSE), technical consistency was rigorously managed across various architectural documents, ensuring coherency and minimizing errors. Furthermore, the preliminary design was developed, with the implementation of the Arcadia Method, supported by the Capella modeling tool. This allowed the digitalization of the system, which was represented by models that contain requirements, architecture, and interfaces between the different parts of the system. At the same time, the preliminary design process was streamlined and completed within an accelerated time frame of 4 months, with weekly sprints driving progress based on the scrum methodology. This case study highlights the effectiveness of Agile Systems Engineering principles to improve the team communication accuracy, communication, and efficiency of satellite systems preliminary design, providing valuable insights for future missions.

Probing the Interfacial Interaction Mechanisms of Nitrogen with Dodecane/Toluene: Implications for Foam Flooding.

Interfacial interactions between deformable bubbles and oil drops have attracted much attention in foam flooding. However, interactions involving nitrogen bubbles have not been reported. In this work, the interaction forces between nitrogen and dodecane/toluene in aqueous solutions were quantified using the atomic force microscopy bubble probe technique. The effects of the solution pH, ionic type, and solution concentration on the interactions were analyzed. The van der Waals (vdW), electric double layer (EDL), and hydrophobic (HB) interactions were involved in the low-concentration solutions. The EDL repulsion in NaCl increased with solution pH, while in CaCl2 and MgCl2, the EDL repulsion in general decreased and then increased with pH, attributed to the adsorption of OH- and divalent cations and their hydration products. The adsorption of divalent cations at the toluene/water interface was pronounced by cation-π interactions. At pH 10, precipitated divalent cation hydroxides at the bubble/water and oil/water interfaces adsorbed more cations, causing the increase of the surface potential. At high salinity, the EDL interaction was suppressed and the vdW repulsion became predominant. The vdW force of nitrogen with toluene was stronger than that with dodecane. Under all of the solution conditions, the attractive interaction could not overcome the total repulsive interaction at the minimum separation, and thus no bubble attachment was observed, which implied that a stable bubble/liquid/oil film was essential for maintaining foam stability. This work provides useful insights into the interfacial interaction mechanisms in nitrogen foam flooding. The findings can be readily extended to other engineering systems such as oil flotation and bubble-oil-water emulsions.

Strategic engineering of cationic systems for spatial & temporal anti-counterfeiting applications in zero-dimensional Mn(II) halides

While spatial and time-resolved anti-counterfeiting technologies have gained increasing attention owing to their excellent tunable photoluminescence, achieving high-security-level anti-counterfeiting remains a challenge. Herein, we developed a spatial-time-dual-resolved anti-counterfeiting system using zero-dimensional (0D) organic–inorganic Mn(II) metal halides: (EMMZ)2MnBr4 (named M−1, EMMZ=1-Ethyl-3-Methylimidazolium Bromide) and (EDMMZ)2MnBr4 (named M−2, EDMMZ=1-Ethyl-2,3-Dimethylimidazolium Bromide). M−1 shows a bright green emission with a quantum yield of 78 %. It undergoes a phase transformation from the crystalline to molten state with phosphorescence quenching at 350 K. Reversible phase and luminescent conversion was observed after cooling down for 15 s. Notably, M−2 exhibits green light emission similar to M−1 but undergoes phase conversion and phosphorescence quenching at 390 K, with reversible conversion observed after cooling down for 5 s. The photoluminescence switching mode of on(green)-off–on(green) can be achieved by temperature control, demonstrating excellent performance with short response times and ultra-high cyclic reversibility. By leveraging the different quenching temperatures and reversible PL conversion times of M−1 and M−2, we propose a spatial-time-dual-resolved photoluminescence (PL) switching system that combines M−1 and M−2. This system enables multi-fold tuning of the PL switch for encryption and decryption through cationic engineering strategies by modulating temperature and cooling time. This work presents a novel and feasible design strategy for advanced-level anti-counterfeiting technology based on a spatial-time-dual-resolved system.

Hydrogen-natural gas fuel blending in a “rich burn” engine with 3-way catalyst

Interest in hydrogen (H2) fuels is growing, with industry planning to produce it with stranded or excess energy from renewable sources in the future. Natural gas (NG) utility companies are now taking action to blend H2 into their preexisting pipelines to reduce greenhouse gas (GHG) emissions from burning NG. Stoichiometric (“rich burn”) NG engines that operate on pipeline NG and will receive blended fuel as more gas utilities expand H2 production. These engines are typically chosen for their low emissions owing to the 3-way catalyst control, so the focus of this paper is on the change in emissions like carbon monoxide (CO) and nitrogen oxides (NOx) as the fuel is blended with up to 30% H2 by volume. The Caterpillar CG137-8 natural gas engine used for testing was originally designed for industrial gas compression applications and is a good representative for most “rich burn” engines used across industry for applications such as power generation, gas compression, and water pumping. A significant greenhouse gas (GHG) emissions reduction is observed as more H2 is added to the fuel. Increasing H2 in the fuel changes combustion behavior in the cylinder, resulting in faster ignition and higher cylinder pressures, which increase engine-out NOx emissions. Post-catalyst CO and NOx both decrease slightly with increasing H2 while operating at the optimal “air-fuel” equivalence ratio (λ). A “rich burn” engine with 3-way catalyst can tolerate up to 30% H2 (by vol.) while still meeting NOx and CO emissions limits. However, at elevated levels of H2, increased engine-out NOx emissions narrow the λ range of operation. As H2 is added to NG pipelines, some “rich burn” engine systems may require larger catalysts or more precise λ control to accommodate the increased NOx production associated with a H2-NG blend. Sudden step-increases in H2 cause dramatic changes in λ, resulting in large emissions of post-catalyst NOx during the transition. Comparable changes in H2 at elevated concentrations cause larger spikes in NOx than at lower concentrations. Better tuned engine controllers respond more quickly and produce less NOx during H2 step-transitions.

Analysis of operation regulation on delay time in long-distance heating pipe systems for practical engineering

The distribution area of the district heating network (DHN) is extensive, and there are inherent time delays and thermal losses in the process of heat transfer through heating pipes. The delay in heat transfer within long-distance heating pipes may result in inadequate heat supply to end-users or excessive energy consumption at the heat source. Therefore, this paper presents a quasi-dynamic model for calculating the transmission delay time in the long-distance heating pipeline. And the model is validated through the measured values obtained from a heating pipeline. The influencing factors of delay time are further discussed, including operating parameters, pipe structure parameters and thermal insulator thickness. Additionally, the impact of pipe delay time in practical engineering is analyzed. In practical engineering, the transmission delay time varies when the pipe structural or operational parameters differ, even under the same outdoor temperature change. The change in inlet water temperature and mass flow rate can impact the change rate of outlet water temperature, thereby influencing the delay time. Furthermore, the delay time exhibited an increase with pipe length, diameter, and thermal insulator thickness; however, the effect of thermal insulator thickness on it was minimal. When the inlet water temperature rose or dropped by 5℃, the delay time grew by more 70 % per 1 km pipe length, about 40 % per 100 mm diameter and less 2 % per 100 mm thermal insulator thickness, respectively.

Assessing and Optimizing Ecological Flow Rates for the Habitat of Zacco platypus in the Tan River

As rivers face growing environmental challenges due to climate change and the construction of artificial structures, it is essential that we improve river ecosystems to maintain their ecological functions and preserve the health of aquatic habitats. The aim of this study was to assess the aquatic ecosystem health of the lower reaches of the Tan River. We employed the Physical Habitat Simulation System and Hydrologic Engineering Center’s River Analysis System to calculate the ecological flow rate based on the weighted usable area (WUA) of Zacco platypus, which is a representative fish species in the Tan River, and the flow rate relationship curves. By analyzing the flow rates in the Tan River across different seasons from 2012 to 2021, we determined that the seasonal optimal ecological flow rate was 10.21–10.27 m3/s. Meanwhile, the WUAs for spring, summer, and autumn and winter were 90–100%, 95–100%, and 75–100%, respectively. Despite meeting the ecological flow criteria for summer, fall, and winter over 50% of the time, spring fell short at 41%; hence, the Tan River flow rates should be secured particularly in spring. This study highlights the urgency of addressing seasonal variations to ensure the overall health of the Tan River ecosystem.

CO2 emissions of fuel-cell battery hybrid system for large ships

ABSTRACT The needs of solid oxide fuel cells (SOFC) and batteries in large ships are analyzed by estimating the amount of fuel consumption and CO2 emissions. Three types of systems are proposed: 1) fuel cells-battery-generator engine system, 2) battery-generator engine system, and 3) generator engine system. This study is based on the time-varying electric power demand and adopted the sequential quadratic programming (SQP) method to find the optimal power distribution of mixed power sources. CO2 emissions in the SOFC hybrid system are 11.6% lower than in the conventional generator engine system, and those in the battery-generator engine system are 5.1% lower than in the conventional system. The reduction of CO2 emissions come from three factors: the operation of the generator engine at a relatively high load rate, the battery sharing the operation of the generator engine, and the high efficiency of the SOFC running. The SOFC hybrid system can be a sustainable technology in large vessels.

USE OF IIoT TECHNOLOGIES IN ENGINE MONITORING AND CONTROL SYSTEMS

Determining the operating parameters of engine systems is very important to ensure its long-term reliability. Modern power plants use a large number of modern electronic components (sensors, controllers, etc.). All systems generate a huge volume of data that must be tracked, processed and analyzed, which in turn creates calls to gateways and servers. However, the current state of development of microcontrollers and their power allow the use of fog computing, which can lead to more efficient use of both the power plant and data transmission systems. Also, the use of modern microcontrollers and fog computing allows modernizing old power plants with minimal effort and creating new information nodes for monitoring the state of nodes and engine systems and easily combining them with systems already existing on the engine. The selection of a microcontroller and justification of its type for the modernization of the fuel system of a diesel engine are considered. Rapid processes occur in the high-pressure fuel system of diesel engines, which can be determined by changes in fuel pressure. For detailed measurement of processes in the fuel system, measurements should be made with a frequency of at least 24 kHz, i.e.: if the crankshaft rotation frequency is 4000 min-1, then 24,000 measurements should be made every second (when registering data after 1 degree of crankshaft rotation). Another indicator that imposes its requirements is the bit rate of the analog-to-digital converter (ADC), which depends on the range of recorded values. For example, an ADC with a resolution of 8 bits is capable of outputting 256 discrete values (0…255). That is, the higher the bit rate, the more sensitive the converter is to signal changes, and 8 bits may not be enough. Thus, even a small number of sensors can generate a huge amount of data. Transmitting large amounts of data is irrational and can lead to data loss and "clogging" of transmission channels, which challenges the computational performance of the microprocessor.

Heavy fuel preparation effects on the operation of a spark ignition unmanned aerial vehicle engine

PurposeThis paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine for unmanned aerial vehicle application.Design/methodology/approachOne-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline and fuels.FindingsThe experimental research has shown performance improvements using fuel preheating via use of auxiliary transfer port fuel injection. Computational simulation has allowed comparisons with auxiliary transfer port injection and direct in-cylinder injection to be made.Practical implicationsWhile some heavy fuel engines are now available for unmanned aerial vehicles the best solution to meet the military equipment single fuel policy remains an area of evolving research. The findings within this study show possibilities for fuel pre-treatment.Originality/valueOne-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline fuels.