Power Engineering Research Articles

Dual-Stage Energy Recovery from Internal Combustion Engines

Waste heat recovery is one of the most investigated solutions for increasing the efficiency of powertrains in the transportation sector. A major portion of thermal energy is wasted via exhaust gases. Almost one third of fuel energy is lost, and its recovery as propulsion energy is a promising goal. Moreover, this enables the increased electrification or hybridization of powertrains, assuming the energy recovered is converted into electrical form and used to fulfill different vehicles’ needs. The present study focuses on a dual-stage energy recovery system designed to enhance the efficiency of internal combustion engines (ICEs) in heavy-duty vehicles (HDVs). The system combines a turbocompound unit for direct heat recovery (DHR) and an organic Rankine cycle (ORC) for indirect heat recovery (IHR). These technologies aim to exploit waste heat from exhaust gases, converting it into electrical energy. In this regard, electrical energy can be stored in a battery for it to be available for the energy needs of powertrains that use hybrid propulsion and for driving pumps and compressors on board, following recent technologies of auxiliaries on demand. The proposed setup was modeled and analyzed under off-design conditions to evaluate energy recovery potential and engine performance impacts. From this point of view, in fact, any device that operates on exhaust gas introduces a pressure loss, increasing engine backpressure, whose effect is an increase in specific fuel consumption. An estimate of this negative effect is presented in this paper based on experimental data measured in a F1C IVECO™ engine. An average net recovery of 5–6% of engine power has been demonstrated, with an important prevalence of the turbocompound with respect to the ORC section. The results demonstrate the viability of integrating DHR and IHR stages, with implications for advancing sustainable transportation technologies.

In-Cylinder Imaging and Emissions Measurements of Cold-Start Split Injection Strategies

Abstract Strategies to mitigate cold-start emissions are critical to meet stringent standards for particulate and regulated gaseous emissions from direct injection spark ignition (DISI) engines. The objective of the current work was to establish an experimental protocol for cold-start studies and to identify the in-cylinder phenomena important during engine warming in terms of engine power and stability and engine-out particulates, NOx, and unburned hydrocarbon emissions. Metal-engine experiments were conducted with ambient intake air temperature and coolant air temperature of 20 °C to quantify the sensitivity of the performance of a single-cylinder engine to timing of a strategy using two injection events per power cycle and late spark ignition. The results showed strong sensitivity to the timing of the second injection event and weak sensitivity to the timing of the first injection. Complementary high-speed imaging experiments were conducted with the same engine where the fuel spray and combustion characteristics were visualized during cold-start split-injection operation. The imaging data showed the sources of particulates were due to fuel impingement on combustion chamber surfaces and due to fuel rich regions, in particular regions where the fuel recondensed due to the conditions associated with late ignition timing. The combination of engine-out particulate and imaging measurements indicated smaller particles (10–20 nm) were associated with fuel impingement on surfaces, and larger particles (20–200 nm) were associated with fuel rich “pockets”.

Study the Effect of Exhaust Manifold Diameter on the Output Performance of a Four-Cylinder Spark Ignition Engine

As modern engine technology has evolved, optimizing engine performance has become a key research focus for the industry in the face of increasingly stringent environmental regulations and growing demand for energy efficiency. The diameter of the exhaust manifold plays a key role in determining engine performance. This study utilized GT-POWER software to develop an engine simulation model aimed at investigating the effects of different exhaust manifold diameters on engine power, torque, and fuel consumption. The results demonstrated that increasing the exhaust manifold diameter within a specified range significantly reduced fuel consumption at lower speeds, with minimal impact on power and torque. However, at moderate to high speeds, enlarging the exhaust manifold diameter led to a significant increase in power output, an increase in peak torque, and a decrease in fuel consumption, resulting in the shift of peak torque and minimum fuel consumption to higher speeds. These findings provide valuable insights for optimizing engine exhaust manifold design.

Infrared signature of aero-engine exhaust plume’s potential core and aircraft surface from direct bottom view

Abstract Low-flying aircraft are susceptible to attacks by ground-launched infrared (IR)-guided man portable air defence system (MANPADS) and surface-to-air missiles (SAM). When seen from direct below, a dual band sensor can lock on to either exhaust plume or aircraft surfaces. Based on the magnitude of the IR signature, the missile can use any one source for the terminal guidance. In this study, the IR signature of the aircraft surface and potential plume core is analysed and compared from direct bottom view in different IR bands. In the Long Wave Infrared (LWIR) band, the surface emission is higher and in the Medium Wave Infrared (MWIR) band the plume emission is higher. The plume (MWIR) emission is higher than the surface (LWIR) emission for low Mach numbers, but as the Mach number increases the plume (MWIR) to surface (LWIR) emission ratio decreases, and at supersonic Mach numbers the surface LWIR signature is higher than the plume MWIR signature. The plume MWIR to surface LWIR ratio further depends on the engine power, altitude of operation and the emissivity of the aircraft surface. In the reheat mode, plume MWIR emission is always higher than the surface LWIR emission. The dual band IR detector can be a combination of short wave infrared (SWIR)-MWIR, SWIR-LWIR, and the MWIR-LWIR band. The MWIR-LWIR dual band combination is the best suited combination of IR windows for a dual band IR sensor/detector for aircraft application.

Assessment of Natural Radioactivity and Trace Element Composition of Coals and Ash and Slag Waste in Kazakhstan

This article systematizes research data on the natural radioactivity of fossil coals and of ash and slag waste from coal power engineering in the context of radioecological safety. The relatively low energy efficiency of the operating thermal power plants in Kazakhstan has a significant impact on the environment. In addition to natural radioactive elements (U238 and its decay products, Th232 and its decay products, and K40), coal combustion waste also contains a significant amount of trace elements that have a negative impact on the atmosphere and the environment. In Kazakhstan, about 67% of electricity is generated by coal power engineering. However, in the process of burning coals, radioactive nuclides are concentrated in ash and slag waste. In the fuel power industry of Kazakhstan, high-ash coals with low concentrations of radionuclides are mainly used. The average contents of uranium and thorium are close to the clarke values. The natural radioactivity of coal and of ash and slag waste from Karaganda GRES-1, which consumes Ekibastuz coals with an ash content of 32–39%, was studied. The average values of the specific activities of U238, Th232, and K40 in 25 coal samples were 27.9 Bq/kg, 19.5 Bq/kg, and 81.0 Bq/kg, respectively. In ash and slag waste, the concentrations of these radionuclides were several times higher. The concentration coefficients of the studied radionuclides varied within the ranges of 4.7–5.5 for U, 3.8–5.7 for Th, and 4.2–8.6 for K40. It was established that during coal combustion in thermal power plants, due to carbon combustion and the removal of volatile compounds, not only natural radionuclides but also many microelements, including toxic ones (Mn, Cd, Ni, Co, Zn, etc.), are concentrated in the ash.

Lubricant Viscosity Impact in Fuel Economy: Experimental Uncertainties Compensation

Climate constraints impose greenhouse gas emissions mitigation, and passenger cars have considerable contributions to contribute to this. To improve the engine efficiency of vehicles equipped with conventional powertrains, many technologies are available but with limited individual contribution. The experimental assessment of some technology regarding fuel economy measurement results is sometimes lower than test uncertainties. This study proposes a methodology to compensate the fuel economy for two test uncertainties: vehicle speed variations and battery recharging. The proposed method can be applied when investigating the effects of different vehicle design changes, including engine power cell design. In this work, the proposed method is demonstrated on the test of two oils: one 5W40, the other 5W20, both without FM. Applying the proposed methodology to experimental results, the expected higher influence of oil viscosity on urban conditions could be observed, and the experimental results presented a much better correlation with the vehicle numerical simulation. Applying the proposed compensation, fuel savings of using the 5W20 in comparison to the 5W40 oil was 3.5% under urban conditions and 2.0% on highways.

Preface: 6th International Conference on Materials Science, Resource and Environmental Engineering (MSREE 2024)

This proceeding includes original and peer-reviewed research papers from the 6th International Conference on Materials Science, Resource and Environmental Engineering (MSREE 2024: http://www.msree.org), held on December 16-17, 2023 in Xi'an, China. The MSREE 2024 conference had three main topics: 1. Material Science and Engineering Applications; 2. Energy Science and Power Engineering; 3. Resource and Environmental Engineering. The aim of MSREE 2024 is to provide a platform for researchers, engineers, and academicians, as well as industrial professionals, to present their research results and development activities in materials science, energy technology, power engineering. It provides opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration. By submitting a paper to MSREE 2024, the authors agreed to the review process and understood that papers undergo a peer-review process. Manuscripts were reviewed by appropriately qualified experts in the field selected by the Conference Committee, who gave detailed comments and-if the submission was accepted the authors would submit a revised version that took into account this feedback. All papers were reviewed using a double-blind review process: authors declared their names and affiliations in the manuscript for the reviewers to see, but reviewers did not know each other’s identities, nor did the authors receive information about who had reviewed their manuscript. The Committees of MSREE 2024 invested great efforts in reviewing the papers submitted to the conference and organizing the sessions to enable the participants to gain maximum benefit. Qingwei Liu, Willie Jefferson Xi’an, China

Experimental study of the effect of the properties of motor oils on the level of torsional vibrations of the shaft line of the Yaroslavets type vessel

The article presents the results of an experimental study of the influence of motor oil properties on the level of torsional vibrations of the propeller shaft of a Yaroslavets-type vessel. The tests were carried out on mooring lines to create the maximum load on the 3D6 main engine using standard MS20 motor oil and oil with copper additives. Torsional vibrations were measured using a certified verified strain gauge complex “Astech Electronics” (Great Britain) installed on the propeller shaft. The study found that the use of oil with copper additives and MS20 oil does not significantly affect the amplitudes of torsional vibrations of the ship’s propeller shaft in the range of crankshaft speeds of the 3D6 main engine from the minimum stable to nominal. It was found that during the startup of the main engine with oil with copper additives, the level of torsional vibrations decreases, which requires research on more powerful marine diesel engines and an assessment of this effect. When using oil with copper additives, a reduction in the overall spectrum of harmonic component amplitude oscillations is achieved, which leads to a positive effect of reducing stress in the crankshaft and gearbox. Torsional vibrations in the elements of the machine-propulsion complex of a Yaroslavets-type vessel when used as a tug do not exceed the permissible values calculated according to the RCO rules, so additional measures to reduce them are not required. Additional experimental studies are needed to assess the effect of lubricating oil with copper additives on the vibroacoustic characteristics of marine diesel engines — vibration level and external noise.

Effect of tire pyrolysis oil and graphene oxide nanoparticles as an additive in the diesel engine.

The majority of industries throughout the world rely largely on fossil fuels as their primary energy source. However, these resources are finite and become scarcer by the day. Therefore, exploring alternative fuels and additives for diesel fuel is imperative to mitigate fuel consumption. A diesel engine powered with different blends of diesel fuel (DF), graphene oxide (GO) nanoparticles, and tire pyrolysis oil (TPO) was used in this investigation. The goal was to undertake in-depth evaluations of performance and emission characteristics. The findings of these investigations were compared to those obtained using neat diesel fuel as a baseline. In the study, diesel fuel blends containing various quantities of graphene nanoparticles (40, 80, and 120mg/L) and 10%, 20%, and 30% TPO were made. A single-cylinder, four-stroke, air-cooled spark-ignition engine was used for testing, with engine speed ranging from 1500 to 3500rpm with an increment of 500rpm. At 3000rpm, the engine running on DT10G80 blend fuel produced 10.46% greater torque than diesel fuel, and at 3500rpm, 11.7% more brake power. The BSFC of the DT10G80, which is 13.33% lower than that of diesel fuel, is the lowest at 2500rpm. When compared to diesel fuel, there are 33.3% and 19.8% fewer CO and NOx emissions, respectively, according to the emission analysis. Finally, combining nanoparticles, waste fuel tire pyrolysis oil, and diesel fuel improves engine power, decreases fuel consumption, and minimizes hazardous gas emissions and particulate matter.

Performance Evaluation and Analysis of a Vehicle

The rapid advancements in technology and the growing demand for personalized solutions have revolutionized the automobile industry. This report introduces a Vehicle Performance and Analysis Application, designed to streamline the process of finding vehicle details based on user-defined parameters. The application provides comprehensive insights into vehicle specifications, performance metrics, and associated company information, enabling users to make well-informed decisions. Additionally, it offers manufacturers and dealers valuable analytics on user preferences and frequently searched criteria. The application features an intuitive search mechanism that allows users to filter vehicles based on parameters such as fuel efficiency, engine power, seating capacity, price range, and more. It also includes a comparison tool to evaluate multiple vehicles simultaneously. For manufacturers and dealers, the app provides real-time data on market trends and user preferences, helping them tailor their offerings and marketing strategies.By integrating advanced technologies such as dynamic database systems and analytical modules, this application enhances the user experience and facilitates data-driven decision-making for companies. The Vehicle Performance and Analysis App thus bridges the gap between consumer demands and market offerings, fostering transparency, efficiency, and innovation in the automobile industry.

Peptidisc-Assisted Hydrophobic Clustering Toward the Production of Multimeric and Multispecific Nanobody Proteins.

Multimerization is a powerful engineering strategy for enhancing protein structural stability, diversity and functional performance. Typical methods for clustering proteins include tandem linking, fusion to self-assembly domains and cross-linking. Here we present a novel approach that leverages the Peptidisc membrane mimetic to stabilize hydrophobic-driven protein clusters. We apply the method to nanobodies (Nbs), effective substitutes to traditional antibodies due to their production efficiency, cost-effectiveness and lower immunogenicity, and we demonstrate the formation of multimeric assemblies termed "polybodies" (Pbs). Starting with Nbs directed against the green fluorescent protein (GFP), we produce Pbs that display an increased affinity for GFP due to the avidity effect. The benefit of this increased avidity in affinity-based assays is demonstrated with Pbs directed against the human serum albumin. Using the same autoassembly principle, we produce bispecific and auto-fluorescent Pbs, validating our method as a versatile engineering strategy to generate multispecific and multifunctional protein entities. Peptidisc-assisted hydrophobic clustering thus expand the protein engineering toolbox to broaden the scope of protein multimerization in life sciences.

Optimizing Supply Chain Management with Real-Time Data Integration Platform

Real-time data integration platforms have emerged as transformative solutions in modern supply chain management, revolutionizing how organizations process, analyze, and act on critical business information. These platforms enable seamless connectivity between suppliers, manufacturers, distributors, retailers, and customers, providing end-to-end visibility and enhanced decision-making capabilities. The evolution from traditional batch processing to real-time integration represents a fundamental shift in supply chain operations, addressing challenges such as data latency, system fragmentation, and operational inefficiencies. Through advanced technological components including sophisticated data ingestion layers, powerful processing engines, and efficient distribution systems, organizations can achieve substantial improvements in inventory management, order fulfillment, and customer satisfaction. The integration of artificial intelligence, edge computing, and blockchain technologies further enhances these capabilities, enabling predictive analytics, automated decision-making, and enhanced security measures. The implementation of these platforms, while challenging, offers significant strategic advantages including improved operational efficiency, reduced costs, and strengthened competitive positioning in the global marketplace.

A NON-SELECTIVE METHOD OF FORMING A DATA BANK ON THE TECHNICAL CONDITION OF THE INTERNAL COMBUSTION ENGINE FUEL SYSTEM OF TECHNOLOGICAL MACHINES IN REAL TIME

BACKGROUND: The economic component of the effective functioning of technological machines consists in their uninterrupted operation when performing various tasks in such industries as construction, road, agriculture, etc. It is currently possible to take into account the variety of operating conditions of technological machines and constantly changing loading modes by using digital technologies that allow creating an array of databases not only in real time, but also for an individual machine. An urgent task is to create methods for collecting information about the operating modes of the machine, the factors causing changes in the efficiency of operation, the development of algorithms for making decisions about maintaining the working condition of all units and systems of the machine, preventing their failures and non-production downtime of the machine as a whole. AIMS: to ensure the effective functioning of a single technological machine by managing the risks of failures, by adjusting the frequency of maintenance and periods of repair and restoration effects based on real-time data on the technical condition and digital processing of decision-making information. MATERIALS AND METHODS: the nature of changes in the technical condition of aggregates and systems of technological machines in the theory of systems is most often considered as random due to the high probability of uncertainty of factorial influence. It is proposed to consider the problem of failure risk management of system elements and aggregates of technological machines using the basic provisions of the theory of emissions of random processes. The object of the study is a diesel engine of a technological machine with an example of monitoring the technical condition of the fuel system. RESULTS: The substantiation of the expediency of performing maintenance and repair and restoration effects of technological machines according to need is presented. The adjustment of the maintenance frequency was carried out based on the results of these changes in the performance of the machine, in particular the internal combustion engine fuel system. To develop an algorithm for the formation of a data array, typical architectures for collecting and processing information using digital platforms for decision-making on the intensity of parameter changes are used, as an example, oscillograms of pressure changes during the operation of the internal combustion engine power system are presented. CONCLUSIONS: A module for diagnosing the technical condition and efficiency of the internal combustion engine of a single technological machine in real time has been developed. It is proposed to introduce an intelligent decision-making system with subsequent transformation into the image of a digital double of failure risk management and control of the efficiency of the machine for various operating conditions.

Compressed Air Vehicle

ct - This paper presents an experimental study of an engine driven by compressed air. The compressed air engine is a modified 100 cc internal combustion engine. The engine is modified from a 4-working stroke to a 2- working stroke engine (power and exhaust) by modification of cam-gear system. A temperature decrease from room temperature to 15 °C was observed at exhaust. The project was successfully manufactured and tested. Experimental analysis were carried out on this modified engine to find out its performance characteristics like brake power, indicated power, torque etc. It should be noted that pressure higher than that currently employed can result in increased engine performance in terms of output power, torque and speed. Nevertheless, the main advantage of this engine is that no hydrocarbon fuel is required that means no combustion process is taking place, thus the compressed air vehicle will play important role in reducing air pollution. Another benefit is that it uses air as fuel which is available abundantly in atmosphere. This study presents the atmospheric air which can be used in vehicles as the main or auxiliary source of power system. Key Words: Compressed air, Alternative Sources of Energy, clean & highly efficient, light weight, Non-polluting.

Statistical analysis of technical specifications of self-propelled reversible plate compactors with different types of engines

Introduction. Reversible plate compactors are soil compaction machines with a flat operating device, having two or more unbalanced shafts and ability to reverse the direction and movement speed. Reversible plate compactors may be driven by gasoline, diesel or electric engines. The efficient operation of reversible plate compactors is only possible with the rational selection of technical specifications, such as oscillation frequency and driving force of the vibration exciter, base plate width, engine power, etc. To establish correlations between the technical specifications of reversible plate compactors, to assess the influence of the engine type on the main parameters and to identify the areas for improving this type of equipment, the statistical analyses was conducted.Materials and methods. 484 models of reversible plate compactors were scrutinized. The information on the models were obtained from official websites of plate compactors manufacturers and their dealers. Data processing was performed in Microsoft Excel.Results. The variation ranges of the main parameters were determined and regression equations for correlations between the oscillation frequency of the vibration exciter, the driving force, the width of the base plate, the relative exciting force and the mass of reversible plate compactors were derived. Correlation coefficients were obtained for each regression dependence. The influence of the engine type on the variation range of reversible plate compactors’ main parameters was analyzed.Conclusion. The type of engine has almost no effect on the parameters of reversible plate compactors in the corresponding mass ranges. Relatively low correlation coefficients let us suggest that manufacturers do not have reliable methods for justification of the technical specifications of reversible plate compactors. The obtained correlations may be recommended for verification of some technical specifications of reversible plate compactors. In recent decades, the values of oscillation frequency and relative exciting force have increased significantly, which affects the nature of interaction between a reversible plate compactor and soil.

Optimizing power and efficiency of a single spin heat engine

Optimizing power and efficiency of a single spin heat engine

DomeVR: Immersive virtual reality for primates and rodents.

Immersive virtual reality (VR) environments are a powerful tool to explore cognitive processes ranging from memory and navigation to visual processing and decision making-and to do so in a naturalistic yet controlled setting. As such, they have been employed across different species, and by a diverse range of research groups. Unfortunately, designing and implementing behavioral tasks in such environments often proves complicated. To tackle this challenge, we created DomeVR, an immersive VR environment built using Unreal Engine 4 (UE4). UE4 is a powerful game engine supporting photo-realistic graphics and containing a visual scripting language designed for use by non-programmers. As a result, virtual environments are easily created using drag-and-drop elements. DomeVR aims to make these features accessible to neuroscience experiments. This includes a logging and synchronization system to solve timing uncertainties inherent in UE4; an interactive GUI for scientists to observe subjects during experiments and adjust task parameters on the fly, and a dome projection system for full task immersion in non-human subjects. These key features are modular and can easily be added individually into other UE4 projects. Finally, we present proof-of-principle data highlighting the functionality of DomeVR in three different species: human, macaque and mouse.

Recet advances in multilevel converter and impedance source converter for electric power engineering

Recet advances in multilevel converter and impedance source converter for electric power engineering

A Review on Ferry Electrification: A Path towards Sustainable Maritime Transport

This paper reviews research and development efforts for ferries' electrification, focusing on energy supply grids, communication networks, charging systems, and energy storage. It analyzes energy storage technologies, battery charging requirements, shore side infrastructure design, power system architecture, and alternative battery charging stations[1]. The study evaluates the effectiveness of using an electric/hybrid ferry boat for tourist transportation in a real case. The optimal system configuration depends on engine power, energy storage, photovoltaic system sizes, and percentage of hybrid or pure electric usage. The analysis can be replicated to other cases, showing the potential of new technologies for sustainable boating and improving passenger service, especially in terms of comfort[15]. One of the most important steps in lowering greenhouse gas emissions and the marine industry's reliance on fossil fuels is the electrification of ships. This analysis examines the technical developments, difficulties, and environmental effects of switching from conventional fossil fuel-powered ships to electric and hybrid ships. The future of fully electric ships, legislative efforts, and how these advancements relate to international sustainability goals are also covered in the study.

Improvement of Unmanned Aerial Vehicles model under surge of Lightning Electromagnetic Pulse developed using Artificial Intelligence based on laboratory measurements in reference to classical regression methods

Unmanned aerial vehicles (drones) are increasingly used in a growing number of applications, both civil and military. Their design is based on low weight, making the presence of shielding a difficult decision between safety and weight. Currently, there are no mathematical models to determine the safety of drones operating near a storm front. Lightning causes an electromagnetic wave of an impulse nature, which may pose a real threat to electronic systems. This work attempts to develop a mathematical model for simulating drones safety in terms of electromagnetic pulses using artificial intelligence-based tools. Actual measurement results collected from four drones were used as training data. They were tested in laboratory conditions using specialized measuring equipment used to test avionics in accordance with international standards such as DO-160. A repeatable surge pulse generator and a data acquisition system allowed us to collect information on how overvoltages propagate inside the drone’s systems. Systems that directly influence its operation were selected for this purpose, such as the power supply system, engine controllers, GPS system, camera and data bus lines. Other works show that most overvoltages are induced in motor coils and antennas. On this basis, a number of formulas and equations were developed to describe the most important elements of the drone, without which its correct operation will not be possible. The results of the analyzes and the mathematical model of the drone based on the examined cases are presented in this work as a complement to real experiments.