Generation Of Engines Research Articles

Analytical solution to incident angle quasi-phase-matching engineering for second harmonic generation in a periodic-poled lithium niobate crystal

Phase matching or quasi-phase matching (QPM) is of significant importance to the conversion efficiency of second harmonic generation (SHG) in artificial nonlinear crystals like lithium niobate (LN) crystal or microstructured nonlinear crystals like periodic-poled lithium niobate (PPLN) crystals. In this paper, we propose and show that the incident angle of pump laser light can be harnessed as an alternative versatile tool to engineer QPM for high-efficiency SHG in a PPLN crystal, in addition to conventional means of period adjusting or temperature tuning. A rigorous model is established and analytical solution of the nonlinear conversion efficiency under the small and large signal approximation theory is obtained at different incident angles. The variation of phase mismatching and walk-off length with incident angle or incident wavelength are also explored. Numerical simulations for a PPLN crystal with first order QPM structure are used to confirm our theoretical predictions based on the exact analytical solution of the general large-signal theory. The results show that the narrow-band tunable SHG output covers a range of 532 nm–552.8 nm at the ideal incident angle from 0° to 90°. This theoretical scheme, fully considering the reflection and transmission at the air-crystal interface, would offer an efficient theoretical system to evaluate the nonlinear frequency conversion and help to obtain the maximum SHG conversion efficiency by selecting an optimum incident wavelength and incident angle in a specially designed PPLN crystal, which would be very helpful for the design of tunable narrow-band pulse nanosecond, picosecond, and femtosecond laser devices via PPLN and other microstructured LN crystals.

Thickness debit effect and multi-factor coupling mechanism of Ni3Al-based single crystal alloy

With the continuous development of aircraft engine generations, single-crystal alloy blades with more complex shapes and reduced wall thickness are urgently requested. However, the deteriorated performance associated with the wall thickness reduction has not been effectively resolved until now. In this research, the creep behavior of a [001]-oriented Ni3Al-based single crystal alloy with a thin-wall thickness was explored under the environment of 980 °C/220 MPa. A multi-factor coupling mechanism was proposed to explain the premature failure of the thin-walled specimen, providing a comprehensive understanding of the reasons behind the occurrence of the thickness debit effect. The study elucidated the influences of surface oxidation, the stress state of TCP phases, pore growth, and crack propagation on the creep performance. The findings serve as valuable theoretical references for the design and related research of future blade materials.

Summarizing Web Archive Corpora via Social Media Storytelling by Automatically Selecting and Visualizing Exemplars

People often create themed collections to make sense of an ever-increasing number of archived web pages. Some of these collections contain hundreds of thousands of documents. Thousands of collections exist, many covering the same topic. Few collections include standardized metadata. This scale makes understanding a collection an expensive proposition. Our Dark and Stormy Archives (DSA) five-process model implements a novel summarization method to help users understand a collection by combining web archives and social media storytelling. The five processes of the DSA model are: select exemplars, generate story metadata, generate document metadata, visualize the story, and distribute the story. Selecting exemplars produces a set of k documents from the N documents in the collection, where k < < N , thus reducing the number of documents visitors need to review to understand a collection. Generating story and document metadata selects images, titles, descriptions, and other content from these exemplars. Visualizing the story ties this metadata together in a format the visitor can consume. Without distributing the story, it is not shared for others to consume. We present a research study demonstrating that our algorithmic primitives can be combined to select relevant exemplars that are otherwise undiscoverable using a conventional search engine and query generation methods. Having demonstrated improved methods for selecting exemplars, we visualize the story. Previous work established that the social card is the best format for visitors to consume surrogates. The social card combines metadata fields, including the document’s title, a brief description, and a striking image. Social cards are commonly found on social media platforms. We discovered that these platforms perform poorly for mementos and rely on web page authors to supply the necessary values for these metadata fields. With web archives, we often encounter archived web pages that predate the existence of this metadata. To generate this missing metadata and ensure that storytelling is available for these documents, we apply machine learning to generate the images needed for social cards with a Precision@1 of 0.8314. We also provide the length values needed for executing automatic summarization algorithms to generate document descriptions. Applying these concepts helps us create the visualizations needed to fulfill the final processes of story generation. We close this work with examples and applications of this technology.

MalFe—Malware Feature Engineering Generation Platform

The growing sophistication of malware has resulted in diverse challenges, especially among security researchers who are expected to develop mechanisms to thwart these malicious attacks. While security researchers have turned to machine learning to combat this surge in malware attacks and enhance detection and prevention methods, they often encounter limitations when it comes to sourcing malware binaries. This limitation places the burden on malware researchers to create context-specific datasets and detection mechanisms, a time-consuming and intricate process that involves a series of experiments. The lack of accessible analysis reports and a centralized platform for sharing and verifying findings has resulted in many research outputs that can neither be replicated nor validated. To address this critical gap, a malware analysis data curation platform was developed. This platform offers malware researchers a highly customizable feature generation process drawing from analysis data reports, particularly those generated in sandbox-based environments such as Cuckoo Sandbox. To evaluate the effectiveness of the platform, a replication of existing studies was conducted in the form of case studies. These studies revealed that the developed platform offers an effective approach that can aid malware detection research. Moreover, a real-world scenario involving over 3000 ransomware and benign samples for ransomware detection based on PE entropy was explored. This yielded an impressive accuracy score of 98.8% and an AUC of 0.97 when employing the decision tree algorithm, with a low latency of 1.51 ms. These results emphasize the necessity of the proposed platform while demonstrating its capacity to construct a comprehensive detection mechanism. By fostering community-driven interactive databanks, this platform enables the creation of datasets as well as the sharing of reports, both of which can substantially reduce experimentation time and enhance research repeatability.

Artificial Intelligence, Academic Misconduct, and the Borg: Why GPT-3 Text Generation in the Higher Education Classroom is Becoming Scary

We explore playfully the capacity of an artificial intelligence text generation engine called GPT-3 to produce credible academic texts. Departing from a concern raised by colleagues about the possibility of using GPT-3 to cheat in academia, particularly at the undergraduate level, we interact with the GPT-3 interface as nerdy novices to learn what it could produce. The outputs from the GPT-3 text generation engine are incredible, at times surprising, and often terrible. We point to ways in which GPT-3 might be used by students to produce written work and reasons why most instructors, most of the time, could see through what GPT-3 has produced (at least for now). In our experiments, we learn that GPT-3 can be a productive collaborator in paper design but wonder if this is ethical. In short, while fun and somewhat addictive to experiment with, we must pay attention to the potential ways that AI text generation may begin to appear in the anthropology classroom.

Investigation of Heat Annealing and Parametric Optimization for Drilling of Monel-400 Alloy

A nickel-based copper alloy known as Monel-400 is extensively applied in many industries including aerospace, marine engineering, and nuclear power generation, owing to its exceptional characteristics such as extreme tensile strength and toughness, excellent corrosion resistance, and the ability to retain shape even at extremely high temperatures. Traditional methods of drilling Monel-400 alloy are difficult due to quick tool wear and poor surface polishing, resulting in expensive machining costs. In this study, a technique called heat annealing was implemented to externally heat-treat the Monel-400 alloy material before the drilling process. Cutting force, surface roughness, and tool wear were used as the responses to investigate the effect of heat annealing and the drilling parameters on the machinability of Monel-400. The results revealed that the cutting force (Fz) and surface roughness (Ra and Rt) could be reduced by 33%, 31%, and 25%, respectively, after annealing at 700 °C compared to the results of the drilled Monel-400 at room temperature. It can be observed that the maximum improvement can reach 42% of Fz, 35% of Ra, and 59% of Rt while annealing Monel-400 at 1000 °C. A significant reduction was observed in the tool wear for machining the annealed material, which minimized the tooling and overall machining cost. Regarding the effects of the drilling process on the considered responses, the results revealed that the spindle speed has a greater effect on the cutting force, whereas the feed rate has the most significant effect on Ra. The significance of the drilling input parameters on the outputs is determined by analysis of the main effect plots and surface plots. Subsequently, the multi-objective genetic algorithm (MOGA) is used to identify the optimal parametric conditions for minimizing the cutting force and surface roughness of the drilled holes. The optimized values achieved via multi-objective optimization are the cutting force, Fz = 388–466 N, and the surface roughness, Ra = 0.17–0.19 μm and Rt = 3–3.5 μm, respectively.

Design and Synthesis of Co-initiators via Base-Catalysed Sequential Conjugate Addition: Application in Photoinduced Radical Polymerisation Reaction.

Applications of photochemistry are becoming very popular in modern-day life due to its operational simplicity, environmentally friendly and economically sustainable nature in comparison to thermochemistry. In particular photoinduced radical polymerisation (PRP) reactions are finding more biological applications and especially in the areas of dental restoration processes, tissue engineering and artificial bone generation. A type-II photoinitiator and co-initiator-promoted PRP turned out to be a cost-effective protocol, and herein we report the design and synthesis of a new efficient co-initiator for a PRP reaction via a barrierless sequential conjugate addition reaction. Experimental mechanistic observations have been further complemented by computational data. Time for newly synthesised 1,2-benzenedithiol (DTH) based co-initiator promoted polymerisation of urethane dimethacrylate (UDMA, 70 %) and triethylene glycol dimethacrylate (TEGDMA, 30 %) in presence of 450 nm LED (15 W) under the aerobic conditions is 38 seconds. Polymeric material has high glass transition temperature, improved mechanical strength (860 BHN) and longer in-depth polymerisation (3 cm).

Assessing Z Generation Engineering Students' Social Media Platform Usage and Safety Awareness

Despite various attempts to enhance community awareness, the number of cybercrime cases continues to rise. A key contributing factor to this trend is the lack of security awareness when using social media platforms. As such, this study aimed to examine the frequency of social media platform use and the level of security awareness among Generation Z engineering students in Malaysia. Using a quantitative approach, a survey-style study was conducted, involving a sample of 410 randomly selected Generation Z engineering students from across Malaysia. Results indicated that Malaysian Generation Z engineering students exhibit moderate levels of security awareness when using social media. Furthermore, Chat and Messaging Network platforms were found to be the most commonly used social media platforms among this group.

3D Woven Composite Applications for the Next Generation of Aircraft Engines

The use 3D woven composites is on the rise, especially in aircraft engine components. OEMs are recognizing the many performance and economic advantages offered by the 3D weaving process, especially in aircraft engine applications that require high damage tolerance. Near net shape preforms with high fiber volume can be produced using the 3D weaving process. 3D weaving also offers the designer with the choice of virtually unlimited fiber architectures and design possibilities. However, a good, reliable and computationally efficient design tool for 3D woven composites is a basic necessity in order to enable the designer to fully exploit the advantages offered by the 3D weaving process. A simple analytical tool like TEXCAD can provide reliable and quick estimates and parametric studies of the 3D stiffnesses and strengths over the full range of fiber architectures that are possible with 3D weaving. Challenges in the use 3D woven composites relate to the lack of structural progressive damage modeling capability, the lack of standards and methods for the quality control, inspection and process control of 3D weaving processes and a lack of a good understanding of the effects of defects and fiber architecture variability on mechanical properties.

Thermodynamic analysis of the thermal and exergetic performance of a mixed gas-steam aero derivative gas turbine engine for power generation

A thermodynamic analysis is performed for an aero derivative gas turbine engine which utilizes steam injection to increase its efficiency. The target was to explore the performance of a high efficiency gas turbine unit for electric power generation without downstream Rankine cycle. A Rankine cycle for exhaust heat recovery is unattractive because of its large response time and cost of investment. The main purpose of this research was to develop a better understanding of how the optimal cycle efficiency is reached, when the steam for injection is generated by use of the turbine exhaust heat. The STIG cycle becomes attractive for grid stabilization because of its low CAPEX and small footprint and response time.A thermodynamic model has been developed to simulate the simple cycle gas turbine, steam generation and effects of steam injection. Reference input parameters for the model are taken for the GE LM6000 turbine as publicly available. The performance of the engine without steam injection as predicted by the model is compared with literature for validation and compares well.The performance of the STIG cycle as a function of operation parameter steam mass flow and design parameters pressure ratio and turbine inlet temperature is investigated and the optimal parameter settings determined. It is found that this type of cycle shows a very specific parameter setting for optimal efficiency. By using steam injection for the chosen turbine and its parameters an efficiency gain of around 11% points and an output power augmentation of 45% can be achieved.

Performance of solar vortex engine integrated with the PV panel: Experimental assessment

Solar energy is one of the most important options for humanity to face the danger of energy depletion and to address the problem of environmental pollution resulting from the use of fossil fuels. The primary goal of the current article study is to present a new design of a Solar Vortex Engine system integrated with a photovoltaic panel. System implementation and analysis were approached and discussed. The system consists of a 3.0 m2 solar collector inclined with a 36° and a cylindrical vortex generator engine with an outer diameter of 40 cm and a height of 30 cm.The outcomes showed that the developed solar vortex engine could generate a circular updraft with the ratio of the tangent to the axial velocity of 2.83 m/s in the upper exit plane of the vortex generation engine. The electrical efficiency of the system containing a horizontal solar panel was higher than that of the system containing a vertical solar panel and reach its highest value of 14% at 10 a.m. Also, the highest thermal efficiency values were 45% for the system without a solar panel. The results confirmed that the presence of solar panels causes a clear decrease in the thermal efficiency of the system. The proposed solar vortex engine design presented and tested in this article is convenient for forming an artificial upward vortex.

Energy, exergy and emission [3E] analysis of Mesua Ferrea seed oil biodiesel fueled diesel engine at variable injection timings

Biofuels can be used in diesel engine for power generation to address the twin problems: fossil fuel depletion and the rise of pollution. In this regard, the present work explores the possibility of enhancement of performance of Mesua Ferrea seed oil biodiesel run diesel Engine through operation at different injection timings and load settings. The investigation is carried out through energy, exergy, and emission (3E) analysis. For experimentation, a research test engine of 3.5 kW is considered. Four injection timings (20° bTDC, 23° bTDC, 25° bTDC, 28° bTDC) and five load settings (20%, 40%, 60%, 80%, 100%) were taken for the test. The results indicate that the retarded injection timing of 20° bTDC results in an improvement of fuel conversion efficiency, as well as a lowering of both exergy destruction and emissions for Mesua Ferrea seed oil biodiesel, run a diesel engine. At injection timing of 20° bTDC for 100% load, the maximum brake thermal efficiencies and maximum exergetic efficiency were found to be 26.11% and 30.32%, respectively under biodiesel mode as compared to 27.76% and 30.74%, respectively for diesel mode. For the same injection timing, the average drop in CO, CO2, and HC emissions were found to be 46.22%, 1.62%, and 39.67%, respectively whereas the average increase of NOX emission was found to be 8.08% in comparison to diesel mode.

Numerical study of the impact of hydrogen addition, swirl intensity and equivalence ratio on methane-air combustion

Abstract Hydrogen-blended fuel is a promising resource for future generations of gas turbine engines, due to its capability of reducing carbon-based emissions. This paper presents a numerical study to assess hydrogen-enriched combustion in a laboratory-scale burner operating at a high turbulence level and under lean and stoichiometric burning conditions. Moreover, a wide range of H2 (up to 90 %) is used for enriching CH4-air combustion in combination with two different swirl levels. The results show that a high swirl intensity results in shorter flames, due to the increased turbulent intensity, which reduces the flame surface area and uniformness the reacting zone. Besides, increasing swirl intensity further increase flame temperature for a given H2-blended fuel. Overall, the results suggest that high swirl intensity in combination to lean mixtures is favorable when using H2-blended fuel with high H2 concentrations. The simulation results also demonstrate that considering radiation heat loss is influential, as it yields a reduction of the outlet temperature by not less than 100 K, bringing down NO x emissions by half.

Determination of the Equivalent Ratio of Optimum Gasifier with Several Types of Biomass

This study aims to create a CFD model aligned with lab test results from previous studies, conduct simulation tests using several types of biomass as input and optimize the operating parameters of various types of biomass to produce optimum syngas. The method used in this research is literature study and modelling using Ansys Fluent software. The results of this study indicate that biomass is a source of new and renewable energy (EBT) which has abundant potential in Indonesia, but its use could be more optimal. Biomass gasification is one of the most promising techniques used to convert solid fuels into useful gaseous fuels, which can be widely used in many households and industrial applications such as power generation and internal combustion engines. This research implies that it can help determine the optimum equivalence ratio and feed rate for a gasifier that utilizes various types of biomass. By finding the optimal combination, the composting process can achieve higher energy efficiency, resulting in more energy being generated from the biomass used. Additionally, by knowing the appropriate equivalence ratio and feed rate, this research can assist in optimizing the biomass composting process in the gasifier.

Investigating thermal shock and corrosion resistance of Inconel 601 super alloy after thermal barrier coating with %8 YSZ powder

Superalloys, which are categorized in three groups as iron-based, nickel-based and cobalt-based, are used especially in high temperature applications. Inconel 601 alloy, a nickel-based superalloy, is widely used in applications such as chemical processing, aerospace, power generation, heat treatment, chemical refining and gas turbine engines. Although the mechanical properties of superalloy materials and their resistance to wear, corrosion and oxidation are better than other metallurgical materials, these properties are not satisfactory in some applications. In such cases, the desired properties can be obtained by applying heat treatment and coating processes to superalloys. In this study, approximately 100, 200 and 300 µm ceramic top coat thickness thermal barrier coating system with NiCrAlY and 8%YSZ powder coating materials, were created for the Inconel 601 substrate material and SEM, EDS and XRD datas are given. Then, electrochemical corrosion test with 3.5% NaCl solution and 8 cycles of thermal shock test at 1200 °C using FCT thermal shock method were applied to the samples. Considering the corrosion rate values and SEM images after the electrochemical corrosion test, it was determined that the sample with the highest corrosion resistance was the sample with a ceramic top coating thickness of 100 µm. The reason for this is that as the coating thickness increases in thermal barrier coatings, the tension increases and accordingly, a change in pore and crack density occurs. The fact that the samples with a ceramic top coating of 100 µm thickness have the highest corrosion resistance can be explained in this way. Considering that the pore and crack ratio decreases due to the sintering effect in the SEM images of the samples after the thermal shock test, but considering that the TGO layer thickness will increase at higher temperatures and longer service conditions, in regards to thermal barrier coating deformation, it was concluded that the samples with 100 and 200 µm ceramic top coating thicknesses were safer in terms of thermal shock.

Multiphysics performance assessment of hydrogen fuelled engines

In the quest for decarbonisation, alternative clean fuels for propulsion systems are sought. There is definite advantage in retaining the well-established principles of operation of combustion engines at the core of future developments with hydrogen as a fuel. Hydrogen is envisaged as a clean source of energy for propulsion of heavy and off-road vehicles, as well as in marine and construction sectors. A source of concern is the unexplored effect of hydrogen combustion on dilution and degradation of engine lubricants and their additives, and consequently upon tribology of engine contact conjunctions. These potential problems can adversely affect engine efficiency, durability, and operational integrity. Use of different fuels and their method of delivery, produces distinctive combustion characteristics that can affect the energy losses associated with in-cylinder components and their durability. Therefore, detailed predictive analysis should support the developments of such new generation of eco-friendly engines. Different fundamental physics underpin the various aspects of a pertinent detailed analysis. These include thermodynamics of combustion, in-cylinder tribological interactions of contacting surfaces, and blowby of generated gasses. This paper presents such an integrated multi-physics analysis of internal combustion engines with focus on hydrogen as the fuel. Such an in-depth and computationally efficient analysis has not hitherto been reported in the literature. The results show implications for lubricant degradation due to the use of hydrogen in the performance of in-cylinder components and the underlying physical principles.

EFFICIENT FORMALISATION OF TECHNICAL REQUIREMENTS FOR GENERATIVE ENGINEERING

AbstractCurrently, engineers need to manually analyse requirement specifications for determining parameters to create geometries in generative engineering. This analysis is time-consuming, error-prone and causes high costs. Generative engineering tools (e.g. Synera) cannot interpret natural language requirements directly. The requirements need to be formalised in a machine-readable format. AI algorithms have the potential to automatically transform natural language requirements into such a formal, machine-readable representation. In this work, a method for formalising requirements for generative engineering is developed and implemented as a prototype in Python. The method is validated in a case example using three products of an automotive engineering service provider. Requirements to be formalised are identified in the specifications of these three products, which are used as a test set to evaluate the performance of the method. The results show that requirements for generative engineering are formalised with high performance (F1 of 86.55 %). By applying the method, efforts and therefore costs for manually analysing requirements regarding parameters for generative engineering are reduced.

Weight Assessment of Marine Diesel Main and Auxiliary Engines

During the conceptual and preliminary ship design stages, designers must ensure that the selected principal dimensions and parameters are good enough to deliver a stable ship (statically and dynamically), besides deadweight and speed. To support this, the initial intact stability of the proposed ship must be calculated, and for that, the lightship weight and its detailed breakdown are necessary to be known. After hull (steel) weight, machinery weight, mainly marine diesel propulsion and power generation machinery, plays a vital role in the lightship weight estimate of a ship directly. It also affects the deadweight, displacement, draft, and trim, which finally influence stability. The correct estimation of respective weights improves calculating a ship’s initial stability, typically designed and built. Hence, it would be advantageous for the ship designer to convince the shipowner. Weight control is not easy, especially since its consequences in terms of deadweight and stability could be disastrous. It should start right at the beginning and control throughout the design and construction phases. Marine diesel main engines (MEs) and auxiliary engines (AEs) of various power output (generators output for AEs), engine speed, and cylinder number of different engine manufacturers are collected. These are analyzed and presented in tabular and graphical forms to demonstrate the possible relationship between propulsion engine weight and power generation engine weight, and their respective power, speed, and power–speed ratio. In this article, the authors have attempted to investigate the appraisal behavior of ME weight and AE weight regarding engine power, generator power, engine speed, and power–speed ratio (independent variables). Further attempts have been made to identify those independent variables that influence the weight of the propulsion engine and power generation engine (dependent variables) and their interrelationships. A mathematical model has thus been developed and proposed, as a guiding tool, for the designer to estimate the weight of main and AEs more accurately during the conceptual and preliminary design stages.

EVOLUTIONARY PERSPECTIVE ON SYSTEM GENERATION ENGINEERING BY THE EXAMPLE OF THE IPHONE

AbstractIndustrial practice shows that products are developed in generations. Innovation success with complex technical systems can only be achieved economically by using existing solutions as references. These references come from predecessors, competitors, and even industry-external sources. The model of SGE – System Generation Engineering describes these relationships. The iPhone is often used as an example of an innovative product developed in generations. Multiple studies have examined the iPhone. However, none of these studies systematically considers the influence of the product context on references and variations. In this contribution, an evolutionary descriptive model based on the model of SGE is applied to 15 iPhone product generations. The central result is an overview of the variation shares over the generations and the relationships between context factors, reference-based variation activities, and innovation success and hypotheses for causalities. This is one of a series of case studies to investigate these causalities. The study showed how the iPhone remained successful in its context: not through a high new development share, but through strategically placed variations and the use of references from various sources.

MODELLING TECHNICAL SYSTEMS IN THE EARLY PHASE: PROPOSING A FORMAL DEFINITION FOR THE SYSTEM CONCEPT

AbstractThe task of developing “concepts” is common in all fields of engineering, especially in the early phases of product development. However, an in-depth literature analysis showed that authors - often depending on different contexts in design research, education, and industry - define the term “concept” in differing ways. The aspect of reference-based development is rarely addressed in existing definitions. This indicates that there is a need for an updated and concise concept definition. In this paper, the authors propose a new definition of the term “system concept” within the context of SGE - System Generation Engineering that incorporates the findings from the literature analysis. The definition was reflected on in two case-studies. The first one contained the system concept for automotive display and operating systems, the second one the system concept for a kinesthetic-haptic VR interface. The proposed definition contains the relevant characteristics identified from the literature review and supports both current activity-based process models and reference-based development, as practical application has shown.