Implementation Of Engine Research Articles

Felsbauplanung mit dem geotechnischen Werkzeugkasten von morgen: Eurocode 7 – Baugrundeigenschaften (EN 1997‐2:2024)

AbstractThis paper presents an overview of the contents of 2nd Generation Eurocode 7 Part 2, highlighting two of the major changes introduced, being the Ground Model and the Rock Engineering implementation. The document is organized from a ground property perspective so that the role of Part 2 and the links with the geotechnical design are much clearer than in the previous edition. Its new title is a clear indication of this idea: ”Ground properties“ including both soil and rock properties. The need to have representative values for the ground properties is the objective of this new Part 2, which is intended to guide designers on the path to obtain those values by means of the Desk Study, Site Inspection, Field Investigation and Laboratory Testing. Given this framework, the paper explains the concepts behind the Ground Model, the main output of the Ground Investigation, which includes the ground profile, the geometric properties of the ground and its layers, groundwater, and the derived values of the ground properties, paying attention of the role of discontinuities in such ground profile. The tasks that form the Ground Investigation and the minimum number of activities to be performed are described. This new version of EN 1997 will include a Rock Engineering perspective for all above items. And finally, the ground properties of the rock material and the rock mass are listed and discussed.

Science Learning in Answering Digital Competency Needs of Preservice Math and Science Teachers in the STEM Context

These study purposes are to map the digital competency of pre-service math and science teachers and investigate how science learning can answer the challenge of digital competencies (DigComp) needs. This research used Rasch Model analysis to make knowledgeability mapping of the subject and analyzed using Wright map output by Winsteps 5.3.4. Data was gathered from a survey of 328 pre-service teachers of science majors, e.g., Biology, Chemistry, Geography, or Math, using the DigComp Framework-Based Questionnaire (DFBQ). The responses were based on respondents’ diverse demographic profiles (gender, region, living area, and field of study). The findings identify several differences in teacher training students’ knowledgeability of digital competencies that the Wright map in the Rasch model can map. Knowledgeability mapping is essential to determine which part of DigComp still needs to be strengthened with science education in the context of Science, Technology, Engineering, and Mathematics (STEM) implementation. The study yields two main conclusions: 1) The mapping study of pre-service math and science teachers’ knowledgeability in the DigComp framework shows Logit Value Person (0.31LVP1.11) and Logit Value Item (LVI 0.66 logits); (0 ≥ LVI ≥ 0.66) that are reflecting a middle to lower level of competency, and 2) Science learning has high potential to address this challenge through its learning strategy implementations. The findings can be recommendations for future research of knowledgeability mapping and policy development and discuss implications for digital competency framework practices.

TABASCO—Topology Algorithm That Benefits from Adaptation of Sorted Compliances Optimization

Although structural topology optimization has been developing for decades, it still plays a leading role within the area of engineering design. Solving contemporary design problems coming from industry requires the implementation of efficient methods and approaches. This stimulates research progress in the development of novel and versatile topology optimization algorithms. To follow these modern trends, an original topology generator has been elaborated and finally built as a Cellular Automaton with original update rules. The motivation for building the algorithm in this way came from the idea of utilizing the benefits of local compliances sorting. This is conducted on two levels: on the global level, the monotonic function mapping local compliances distribution is defined based on their sorted values; on the local level, for each cell, the compliances are sorted within the cell neighborhood. The three largest absolute values are selected, and these are the basis from which to formulate Cellular Automata update rules. These original rules can efficiently control the generation of structural topologies. This technique is somewhat inspired by the grey wolf optimizer strategy, wherein the process of updating design variables refers to the positions of the three best fitted wolves. It is proposed that we refer to the topology algorithm that benefits from the adaptation of sorted compliances optimization as TABASCO. The developed algorithm is a modified version of the flexible Cellular Automata one presented previously. The implemented extension, regarding the local level cell sorting, allows us to improve the resulting compliance values. The advantages of the algorithm, both from numerical and practical engineering points of view, as compared to the others developed within the field, may be gathered as follows: the algorithm works based on simple update rules, i.e., its numerical implementation is not complicated; it does not require gradient computations; filtering techniques are not needed; and it can easily be combined with professional structural analysis programs which allow engineering applications. The developed topology generator has been linked with ANSYS to show that it can be incorporated into a commercial structural analysis package. This is especially important with respect to the engineering implementations.

Co/Co3ZnC heterojunction entangled with self-grown N-doped carbon nanotubes for hydrogen evolution reaction in both acidic and alkaline media

The investigation of economically viable and effective electrocatalysts holds paramount importance in attaining sustainable progress in the production of hydrogen through water electrolysis. Despite notable progress in catalysts based on transition metals, their efficacy falls short of meeting the demands of industrial applications. The implementation of heterogeneous junction engineering emerges as a strategic approach to augment the efficiency of catalysts in water electrolysis, as it allows for the manipulation of the electronic structure of materials via interfacial effects. This study successfully synthesized a Co/Co3ZnC heterojunction intertwined with self-grown N-doped carbon nanotubes (N-CNTs) using solid-phase grinding combined with high-temperature pyrolysis. The optimized Co/Co3ZnC-2 complex, benefiting from the synergistic effect between the heterojunction and the CNTs framework, exhibited favorable hydrogen evolution performance. Specifically, it achieved overpotentials of only 261 mV and 226 mV at 10 mA cm−2 under acidic and basic conditions, respectively. Consequently, this study presents a pioneering method for producing heterogeneous electrocatalysts by synergistically utilizing the capabilities of various transition metal compounds, thereby contributing to the advancement of their application in the field of energy conversion.

Sustainable Transformation In the Construction Industry: Reducing Environmental Impact and Enhancing Cost Performance through Waste Utilization and Lean Construction

This research aims to improve cost performance and reduce environmental damage in the construction industry in Indonesia through the implementation of value engineering and lean construction methods. Through a case study on high-rise building construction, the research findings reveal that utilizing concrete waste as a substitute for formwork and applying lean construction practices can achieve cost savings of 55.83% compared to the initial plans. Furthermore, this approach provides additional benefits such as increased construction efficiency, utilization of more sustainable resources, and enhanced corporate reputation in terms of environmentally-friendly practices. The results of this research contribute to achieving zero waste in the construction industry, improving cost performance, and actively participating in global environmental conservation efforts. Moreover, the study has the potential to enhance the sustainability of the construction industry in Indonesia and provide long-term positive benefits.

Reinforcement Learning for Multiaircraft Autonomous Air Combat in Multisensor UCAV Platform

Autonomous air combat has received significant attention from researchers working on artificial intelligence (AI) applications. Most previous research on autonomous air combat has focused on one-on-one air combat scenarios in which air combat situational information is considered to be precisely observable. However, most modern air combats are conducted in formations, where air combat situational information is obtained from multiple sensors. Therefore, we introduce a novel automated maneuver decision architecture for close-range multi-aircraft air combat scenarios under the multi-sensor UCAV platform that can handle air combat scenarios with variable-sized formations. Then, a multi-agent reinforcement learning algorithm is proposed to obtain the strategy. The training performance of the training algorithm is evaluated and the obtained strategy is analyzed in different air combat scenarios it is found that these formations exhibit effective cooperative behavior in symmetric and asymmetric situations. Finally, we give ideas for the engineering implementation of a maneuver control architecture. This study provides a solution for future multi-aircraft autonomous air combat.

Performance study of an enhanced fully optical generalized spatial modulation free-space opticalsystem based on serial unmanned aerial vehiclerelay.

This paper proposes an enhanced fully optical generalized spatial modulation (EFOGSM) free-space optical (FSO) system based on serial unmanned aerial vehicle (UAV) relaying under M distribution. The relay transmission mode of the system is decode-and-forward (DF), and two spatial diversity receiving schemes were considered at the receiver of the system. In the atmospheric channel modeling, the angle of arrival (AoA) jitter was introduced to represent the effect of UAV random jitter in the air on the channel, together with three important factors: path loss, pointing error, and atmospheric turbulence. Under the joint influence of the four fading factors, the probability density function expression of the joint fading channel under the new M distribution was derived, and the upper bound of the average bit error rate of the serial UAV-relaying EFOGSM FSO system was derived. The influence of key factors, such as the number of UAV relay nodes, the position distance of UAV, the field of view parameters of the receiver, the direction deviation, and the data transmission rate on the system performance, was analyzed by simulation under weak and strong turbulence. Monte Carlo simulation verified the correctness of the numerical calculation and simulation. This study provides a good theoretical basis for the engineering implementation of a serial UAV relay EFOGSM FSO system.

ANALYSIS OF THE CURRENT STATE OF WARNING OF EMERGENCY SITUATIONS IN THE TERRITORIES OF UKRAINE WHICH WERE SUFFERED BY ROCKET AND ARTILLERY IMPACTS

The author created an array of soil disturbances as a result of military operations. Physical and chemical exposure lead to a drastic increase in dangerous factors. Dangerous factors to local (in the worst case scenario to background) changes in indicators of physical and chemical properties (condition) of soils, they have a long-term nature of danger to the soil environment and pose a danger to the population and territories. The author established that there is a primary accumulation of pollutants in the soil with subsequent redistribution both in the soil itself and in other environments - surface and underground waters. The process of modeling the spread of pollutants is a complex task due to the need to take into account many variables in time and space, physical and chemical parameters of the soil, as well as environmental conditions and the form of pollutants. Scientific developments in the field of monitoring and ecological-geochemical assessment of soil conditions are fragmentary in nature. To date, no universal methodologies have been created for assessing the safety of soils in territories affected by war and approaches regarding the permissible level of their pollution for the prevention of emergency situations. Research should be conducted using a complex of field, remote and laboratory methods. The author determined that the development of new organizational and technical methods of emergency prevention in territories that have suffered missile and artillery damage, based on comprehensive forecasting, monitoring and modeling of soil hazards, should be based on unified methodological positions regarding the place and role of the processes of prevention, prevention, localization and liquidation in the structure of the general process of combating emergency situations. The methodologies were previously tested in a number of works on the development and implementation of organizational, operational engineering and information methods for the prevention of emergency situations of various types of occurrence and spread. Keywords: military-technogenic load, soil pollution, solid metals, emergency happening, prevention of emergency situations.

Spatio-Temporal Changes in Forest Area and Its Ecosystem Service Value in Ganzi Prefecture, China, in the Period 1997–2017

It is possible to manage the forest ecosystem and promote sustainable development by keeping track of spatio-temporal fluctuation in the forest area and its ecosystem service value (ESV). The forest ecology of Ganzi Tibetan Autonomous Prefecture (Ganzi Prefecture), which is located in the northern Hengduan Mountains region, i.e., China’s most important ecological functional area, has seen significant alteration during the past 20 years. However, little is known about how the forest and its ESV evolve. We obtained data regarding Ganzi Prefecture’s forests using visual interpretation of remote sensing images derived from 1997, 2007, and 2017, and we evaluated the spatial–temporal changes in the forest ESV from 1997 to 2017 using global value coefficients and adjusted local value coefficients. The results revealed that (1) from 1997 to 2017, the forest area of Ganzi Prefecture increased by 6729.95 km2, and the forest growth rate was 336.50 km2/a, while (2) from 1997 to 2017, the forest ESV in Ganzi Prefecture experienced an overall increase of 257.59 × 108 yuan. The primary driver of the forest ESV increase was the implementation of forestry ecological engineering and protection policies. (3) Finally, the spatial distribution of the forest ESV revealed that the forest ESV density increased during this period, with the most significant increase occurring in Yajiang. The forest ESV was scattered with the highest density in Yajiang and the lowest density in Shiqu. This study emphasizes how crucial forest ecosystems are to Ganzi Prefecture’s mechanisms for maintaining life. It provided a scientific basis for the sustainable management of the forest ecosystem in the Hengduan Mountains.

Diagnosing Cracks in the Injector Nozzles of Marine Internal Combustion Engines during Operation Using Vibration Symptoms

In the operation of internal combustion engines, despite technical state monitoring, some cracks that develop in metal components go undetected, leading to secondary, critical, or degradation damage. The diagnostic systems used in floating objects mainly use quasi-static thermodynamic signals, which alert operators too late about emerging damage. Although various methods have been developed to detect cracks in internal combustion engine components, the effectiveness and implementation of the proposed methods are not satisfactory. Therefore, this article presents the use of selected vibration and in-cylinder pressure signals to diagnose the development of damage in some components of marine diesel engines. The investigations were conducted under the natural conditions of the operation of sea-going vessels during port-handling operations. During these investigations, it was possible to observe clear changes in the values of diagnostic symptoms, which corresponded to the development of damage. The developing damage detected in the study involved cracks in injector nozzles manufactured from alloy steel. Despite advances in design, materials, and manufacturing technology, injector nozzle cracks still occur. The diagnostic symptoms used to detect damage development were the amplitude and spectral and wavelet measurements of vibration acceleration signals. This work aimed to search for crack-oriented methods of signal analysis, for example, computer visualization and the recording of diagnostic parameters in various domains. Decimation, windowed, time, amplitude, and time-frequency domain analyses; wavelet statistics; color analysis; and machine learning were used for classification using artificial neural networks. Experimental investigations showed the possibility of diagnosing the development processes of damage to marine diesel engines. The advanced signal processing methods used made it possible to obtain many signal measurements, from which the most useful diagnostic symptoms were selected. The new symptoms found with decimation, time-domain windowed analysis, and Haar wavelet statistics were more useful than the existing ones.

Practical AI Cases for Solving ESG Challenges

Artificial intelligence (AI) is a rapidly advancing area of research that encompasses numerical methods to solve various prediction, optimization, and classification/clustering problems. Recently, AI tools were proposed to address the environmental, social, and governance (ESG) challenges associated with sustainable business development. While many publications discuss the potential of AI, few focus on practical cases in the three ESG domains altogether, and even fewer highlight the challenges that AI may pose in terms of ESG. The current paper fills this gap by reviewing practical AI applications with a main focus on IT and engineering implementations. The considered cases are based on almost one hundred publicly available research manuscripts and reports obtained via online search engines. This review involves the study of typical business and production problems associated with each ESG domain, gives background details on several selected cases (such as carbon neutrality, land management, and ESG scoring), and lists challenges that the smart algorithms can pose (such as fake news generation and increased electricity consumption). Overall, it is concluded that, while many practical cases already exist, AI in ESG is still very far away from reaching its full potential; however, one should always remember that AI itself can lead to some ESG risks.

Carbon Emission Prediction Model for the Underground Mining Stage of Metal Mines

At present, the carbon emissions in China’s metal mining industry can be calculated based on the amount of energy consumed in the mining process. However, it is still difficult to predict the carbon emissions before implementation of mining engineering. There are no effective approaches that could reasonably estimate the amount of carbon emissions before mining. To this end, based on the ‘Top–down’ carbon emission accounting method recommended by the Intergovernmental Panel on Climate Change (IPCC), this study proposes a model to predict the greenhouse gases emitted in seven carbon-intensive mining stages, namely, drilling, blasting, ventilation, drainage, air compression, transportation, and backfilling. The contribution of this model is to enable a prediction of the accumulation of greenhouse gases based on the mining preliminary design of mine, rather than on the consumption of energy and materials commonly used in recent research. It also establishes the amount of carbon emissions generated by mining per unit cubic meter of ore rock as the minimum calculation unit for carbon emissions, which allows for the cost and footprint of carbon emissions in the mining process to become clearer. Then, a gold–copper mine is involved as a case study, and the greenhouse gas emissions were predicted employing its preliminary design. Among all the predicted results, the carbon emissions from air compression and ventilation are larger than others, reaching 22.00 kg CO2/m3 and 10.10 kg CO2/m3, respectively. By contrast, the carbon emissions of rock drilling, drainage, and backfilling material pumping are 5.87 kg CO2/m3, 6.80 kg CO2/m3, and 7.79 kg CO2/m3, respectively. To validate the proposed model, the calculation results are compared with the actual energy consumption data of the mine. The estimated overall relative error is only 5.08%. The preliminary predictions of carbon emissions and carbon emission costs in mining before mineral investment were realized, thus helping mining companies to reduce their investment risk.

THE DEVELOPMENT OF A MATHEMATICAL MODEL FOR THE DESIGN OF INTERNAL COMBUSTION ENGINE RADIATORS AND IMPLEMENTATION

Bu çalışmada, içten yanmalı motorlar için yassı su boruları ve düzlem kanatçıklardan oluşan bir radyatörün matematik modeli ve tasarım yöntemi geliştirilmiştir. Geliştirilen matematik modelde radyatörün kanatçıklı borulardan oluştuğu kabul edilmekte ve tasarım işinin özünü kanatçıklı boruların uzunluğunun ve sayısının belirlenmesi oluşturmaktadır. Geliştirilen matematik model ve tasarım yöntemi kullanılarak 100 kW ısı transferi kapasitesi olan bir radyatörün fiziki boyutları araştırılmıştır. Düzlem kanatçıkların arasındaki en uygun mesafenin 0.85-1.05 mm aralığında ve hava akış hızının 5-10 m/s aralığında olabileceği belirlenmiştir. Bu durumda, kanatçıkların arasındaki hava akışı laminer rejimde gerçekleşmekte olup, kanatçıkların yüzeyindeki ısı taşınım katsayısı 100 W/m2K civarında olmaktadır. Kanatçıkların yapımında 0.25 mm kalınlığında alüminyum levha kullanıldığında, kanatçıkların ısıl verimi %90 ın üzerine çıkmaktadır. Motor soğutma suyunun radyatöre giriş ve radyatörden çıkış sıcaklıkları arasındaki fark 15 °C kabul edildiğinde radyatörün en uygun hacmi 25 litre olarak belirlenirken, sıcaklık farkı 10 °C yapıldığında 22.5 litre olarak belirlenmektedir. Tasarım ölçülerine göre hava fanı gücünün 1000-2000 W aralığında olabileceği belirlenmiştir. Ayrıca, su devirdaim pompası gücünün 10 W ın altında kaldığı tespit edilmiştir.

ShapeGraMM: On the fly procedural generation of massive models for real-time visualization

In this study, we propose ShapeGraMM (Shape Grammar for massive models), an expandable grammar that procedurally generates geometries in real-time to create 3D scenes of massive models. Procedural modeling has attracted attention for its ability to quickly create 3D scenes using a compact representation, which stores generation rules rather than an explicit representation of the scene. Our work is an extension of the Computer Generated Architecture (CGA) shape grammar specification. We introduce rules that will take the visibility of the camera into account and decide whether or not it should continue to generate. ShapeGraMM explores the repetitions and patterns present in massive models, helping it render scenes, reduce its memory footprint, and procedurally process the scene efficiently. We propose an engine implementation that generates scenes on the fly using ShapeGraMM, followed by its evaluation using massive real-world models. We conducted a case study testing our solution with large-scale CAD models of the oil & gas industry in the web context, which is a more limited platform than the desktop. In contrast to random models commonly generated by procedural generation methodologies, the original models of our study were modeled in a non-random method. Our results show that the solution has high performance and maintains a compact representation of the models offline and in runtime. The procedural engine renders a massive scene containing over 11 million objects at interactive frame rates.

A Generative Design Method for Typical Structural Parts of Aircraft

Typical structural parts of aircraft are the main frame of the aircraft and the carrier of other parts and equipment. Their good design is the basis to ensure the overall performance of aircraft and reduce maintenance costs. If the selection estimation, parameter setting, and model normative inspection of typical structural parts are carried out manually, the design quality and efficiency of large quantities of structural parts will be low especially. In this paper, a generative design method for typical structural parts of aircraft is proposed. Based on the introduction of the design framework, the intelligent design of 3D models for typical structural parts of aircraft is elaborated by taking shear slices of aircraft as an example. It includes the intelligent recommendation of the structural scheme, intelligent design of structural parameters, and intelligent generation of the 3D model. Engineering implementation shows that the proposed method greatly improves the design efficiency and the overall quality of the aircraft.

SHCT: segmented helical computed tomography based on multiple slant source-translation.

Micro-computed tomography (Micro-CT) is inevitably required to inspect long large objects with high resolution. It is well known that helical CT solves the so-called "long object" problem, but it requires that the measured object be strictly located in the lateral field of view (FOV). Therefore, developing a novel scanning method to extend the FOV in both the lateral and axial directions (i.e., the large helical FOV) is necessary. Recently, due to the application of linearly distributed source arrays and the characteristics of easy extension of the FOV and engineering implementation, straight-line scanning systems have attracted much attention. In this paper, we propose a segmented helical computed tomography (SHCT) based on multiple slant source-translation. SHCT can readily extend the helical FOV by adjusting the source slant translation (SST) length, pitch (or elevation of the SST trajectory), and number of scanning circles. In SHCT, each projection view is truncated laterally and axially, but the projection data set within the cylindrical FOV region is complete. To ensure reconstruction efficiency and avoid the lateral truncation, we propose a generalized backprojection-filtration (G-BPF) algorithm for SHCT approximate reconstruction. Experimental results verify the effectiveness of the proposed SHCT methods for imaging large and long objects. As the pitch decreases, the proposed SHCT methods can reconstruct competitive, high-quality volumes.

Evaluation of Long-Term Fermentation Performance with Engineered Saccharomyces cerevisiae Strains

The performance of a microbial fermentation on an industrial scale is subjected to the robustness of the strain. Such strains are genetically engineered to optimize the production of desired compounds in minimal time, but they often fail to maintain high productivity levels for many generations, hindering their effective application in industrial conditions. This study focused on assessing the impact of genomic instability in yeasts that were engineered to produce a fluorescent output by incorporating a reporter gene at one or more genomic locations. The fermentation performance of these strains was evaluated over 100 generations in a sequential batch set-up. In order to bridge the gap between strain engineering and industrial implementation, we proposed the use of novel, host-specific parameters to standardize the strain robustness and evaluate potential improvements. It was observed that yeasts carrying multiple copies of the reporter gene exhibited a more pronounced decrease in output, and the genomic integration site significantly influenced the production. By leveraging these new, host-specific parameters, it becomes possible to anticipate strain behavior prior to incurring substantial costs associated with large-scale production. This approach enhances the economic viability of novel microbial fermentation processes and narrows the divide between laboratory findings and industrial applications.

Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles

As the process of urbanization continues to accelerate, the demand for sustainable cities has become more critical than ever before. The incorporation of electric vehicles (EVs) is a key component in creating sustainable cities. However, the development of smart cities for EVs entails more than just the installation of charging stations. Software engineering plays a crucial role in realizing smart cities for electric vehicles. This paper examines the role of software engineering in the creation of smart cities for electric vehicles, the techniques utilized in electric vehicle charging infrastructure, the obstacles faced by software engineers, and the future of software engineering in sustainable cities. Specifically, the paper explores the significance of software engineering in integrating EVs into the transportation system, including the design of smart charging and energy management systems, and the establishment of intelligent transportation systems. Additionally, the paper offers case studies to demonstrate successful software engineering implementations for smart cities. Finally, the paper concludes with a discussion of the challenges that software engineers encounter in implementing intelligent transportation systems for EVs and provides future directions for software engineering in sustainable cities.

Exploring valley polarized transport in graphene bilayer flakes

Valleytronics offers new routes to explore possible dual electronic responses related to the valley origin of the carriers. Graphene is known as an optimal material for devices based on valley-filter transport due to the double Dirac cones. Here we focus on understanding the role played by geometrical spatial details in the valley-dependent transport of bilayered graphene flakes, with long length, simulating nanoribbons. Flakes of different widths are considered at the stacking region. We also explore changing the valley transmission when a bias potential is applied. A tight-binding Hamiltonian is used to model the system, and the conductance is obtained by Landauer-Büttiker’s formalism and recursive Green’s function method. Our findings show that considering different bilayered graphene flake widths produces valley-polarized transmissions due to the presence of edge states. Furthermore, the corresponding energy range for which the valley filter occurs depends on the width asymmetries details. The theoretical analysis presented here indicates a potential route for valley-filter transmission scenarios of relatively easy engineering implementation.

A Thermal, Mechanical, and Materials Framework for a Shape Memory Alloy Heat Engine for Thermal Management.

Shape memory alloy (SMA) heat engines possess an inherent property of sensing a change in temperature, performing work, and rejecting heat through the shape memory effect resulting from a temperature-induced phase transformation. This work presents a framework for the design and implementation of an SMA-based Stirling heat engine for maximum torque or speed incorporating and combining mechanical, thermal, and material aspects. There is a growing need for such engines for reliable thermal management and energy recovery in both ground and space applications. Mechanical aspects were addressed from force balances in the SMA element and focused on the resulting stress distribution. Thermal aspects considered heat transfer between the SMA element and both the heat source and the heat sink. Materials aspects considered the chemical, elastic, and frictional contributions to the enthalpy of the transformation. The roles of nano- and microstructure through composition, precipitates, variant interfaces, training, cycling, texture, defects, nucleation sites (bulk vs. surface), and multi-step transformations (e.g., a trigonal R-phase transformation) in NiTi based-alloys are also emphasized. The aforementioned aspects were combined to present a figure of merit to aid in the design and implementation of a Nitinol Stirling heat engine operating to maximize torque or maximize speed.