Simulation Tool Research Articles

A computational materials science paradigm for a Course-based Undergraduate Research Experience (CURE)

Abstract Course-based Undergraduate Research Experiences (CUREs) bring the excitement of research into the classroom to improve learning and the sense of belonging in the field. They can reach more students, earlier in their studies, than typical undergraduate research. Key aspects are: students learn and use research methods, give input into the project, generate new research data, and analyze it to draw conclusions that are not known beforehand. CUREs are common in other fields but have been rare in materials science and engineering. I propose a paradigm for computational material science CUREs, enabled by web-based simulation tools from nanoHUB.org that require minimal computational skills. After preparatory exercises, students each calculate part of a set of closely related materials, following a defined protocol to contribute to a novel class dataset which they analyze, and also calculate an additional property of their choice. This approach has been used successfully in several class projects. Graphical abstract

Matlab-Simulink Model of CHMT for Internal Climate in Greenhouses

Over the past twenty years, Kenya's food security has been threatened by the sub-division of land into tiny areas and the clearance of forests to make way for settlement. These actions have an impact on soil moisture, rainfall patterns, and regional temperature changes. Clear response plans and adaption techniques have been required to address the threats that have arisen. Greenhouse farming, where warmer temperatures are attained and the impact of unfavourable weather conditions on plants is mitigated by the enclosure, is one strategy being used to combat the production of food and climate change. Nevertheless, crop production and quality are negatively impacted by traditional techniques of regulating temperature and humidity through arbitrary opening and closing of the greenhouse walls. In light of this, the goal of this research was to enhance greenhouse farming as it exists today by implementing a dynamic, adjustable system that would create ideal climate conditions for plant growth. This mostly entailed controlling the greenhouse's humidity, temperature, and vapour pressure deficit to the ideal ranges needed by various plants. The humidity and air temperature within the greenhouse were the controlled microclimate conditions. These were accomplished by simulating the convectional heat transfer and mass transfer that occur inside the greenhouse to control the temperature and humidity, and by developing mathematical model utilizing differential equations. Proportional Integral Derivative (PID) was utilized to automatically modify SIMULINK, a block-based modelling and simulation tool. Regardless of the different external conditions, the numerical values for internal temperature and humidity were calculated and graphically depicted. The model made it possible to modify the outcomes according to the needs of the plant. To increase crop productivity in greenhouse farming, it was suggested that a physical prototype model be constructed and integrated into the greenhouse construction.

Open-Source Data Formalization through Model-Based Systems Engineering for Concurrent Preliminary Design of CubeSats

Market trends in the space sector suggest a notable increase in satellite operations and market value for the coming decade. In parallel, there has been a shift in the industrial and academic sectors from traditional Document-Based System Engineering to Model-based systems engineering (MBSE) combined with Concurrent engineering (CE) practices. Due to growing demands, the drivers behind this change have been the need for quicker and more cost-effective design processes. A key challenge in this transition remains to determine how to effectively formalize and exchange data during all design stages and across all discipline-specific tools; as representing systems through models can be a complex endeavor. For instance, during the Preliminary design (PD) phase, the integration of system models with external mathematical models for simulations, analyses, and system budgeting is crucial. The introduction of CubeSats and their standard has partly addressed the question of standardization and has aided in reducing overall development time and costs in the space sector. Nevertheless, questions about how to successfully exchange data endure. This paper focuses on formalizing a CubeSat model for use across various stages of the PD phase. The entire process is conducted with the exclusive use of open-source tools, to facilitate the transparency of data integration across the PD phases, and the overall life cycle of a CubeSat. The paper has two primary outcomes: (i) developing a generic CubeSat model using Systems modeling language (SysML) that includes data storage and visualization through the application of Unified modeling language (UML) stereotypes, streamlining in parallel information exchange for integration with various simulation and analysis tools; (ii) creating an end-to-end use case scenario within the Nanostar software suite (NSS), an open-source framework designed to streamline data exchange across different software during CE sessions. A case study from a theoretical academic space mission concept is presented as the illustration of how to utilize the proposed formalization, and it serves as well as a preliminary validation of the proposed formalization. The proposed formalization positions the CubeSat SysML model as the central data source throughout the design process. It also supports automated trade-off analyses by combining the benefits of SysML with effective data instantiating across all PD study phases.

Evaluating drivers and predictability of catch composition in a highly mixed trawl fishery using stacked and joint species distribution models

Evaluating drivers and the predictability of catch is valuable for the management of mixed fisheries. Drivers can represent or help to identify levers for management and predictable catch compositions are a key component of simulation tools and dynamic management strategies. But modelling mixed fisheries can be challenging due to the large number of taxa, and analysis typically focuses on a few key species or highly aggregated taxa.Here we employ seven types of stacked and joint species distribution models to explore the drivers and predictability of trawl-level catches in an ocean prawn trawl fishery, in New South Wales, Australia. Catch data was sourced from an observer program, with 130 taxa able to be modelled. The main drivers of catch composition were latitude, depth, and seasonality represented here by water temperature. Water column mixing, lunar illumination, and fishing effort were also important for some taxa. Up to 60–80 taxa were predicted with good predictive skill (AUC>0.8, >35 % decline in mean absolute error relative to an intercept-only model), and an additional 40–60 taxa were predicted with lower but still useful predictive skill (AUC>0.7, 25–35 % decline in error). However, the level of predictive skill varied considerably among model type.The best framework for prediction was stacked random forests using a hurdle modelling approach, followed by a spatial joint species distribution model. Our results show that predictive models at a fine spatial-temporal and taxonomic resolutions can be a viable information tool for highly mixed fisheries, but these tools ultimately need to be tested against specific management objectives and performance metrics, such as spatial closures and bycatch:target catch ratios.

Integrated attrition model of mechanical-thermal-reaction for CaCO3/CaO thermochemical energy storage

Fluidized bed reactors have become a pivotal trend in the future development of thermochemical energy storage. However, high temperatures and chemical reactions exacerbate particle attrition in fluidized bed reactors, affecting particle cyclic stability and reducing energy storage efficiency. This study conducted experiments under three different temperature conditions to compare and investigate the attrition mechanisms of CaCO3/CaO particles. The contributions of mechanical forces from collisions, thermal stress due to uneven cooling and heating, and chemical stress from cyclic reactions to particle attrition are analyzed. The edge effects caused by sphericity dominate the attrition behavior during the initial period of fluidization. High-temperature thermal stress significantly weakens the attrition resistance of the particles, while repeated chemical cycling degrades the internal skeletal structure of the particles, lowering the fracture threshold. Based on fitting experimental data, a comprehensive numerical model for predicting particle attrition has been developed and improved by incorporating factors such as edge effects from sphericity, thermally induced stress, and chemically driven fragmentation. Through validation, the model effectively predicts particle attrition behavior in thermochemical storage process, providing a simulation tool for in-depth research on particle stability in thermochemical energy storage field.

READ: Resource efficient authentication scheme for digital twin edge networks

In recent vigorous developments, digital twin edge networks (DITEN) have emerged as a network paradigm to improve network communication efficiency. Given that Web 3.0 technologies promise secure decentralized data storage and effective information exchange, it is feasible to construct a wireless edge intelligence-enabled Web 3.0 physical infrastructure through DITEN. However, DITEN encounters various security threats related to communication and authentication, and establishing a secure and cost-effective authentication scheme for confidential access to physical entities poses a significant challenge. To tackle this issue, in this article, we introduce READ, a provably secure multi-factor user authentication scheme tailored for DITEN in industrial applications. Using designed ASCON cryptography primitive cipher suite, physical unclonable functions, extended Chebyshev chaotic maps, one-way secure collision-resistant hash functions, and lightweight bitwise exclusive-or operations, READ enables mutual authentication and session key negotiation among mobile users, smart gateways, and smart industrial devices. Rigorous security assessments, conducted through the real-or-random (ROR) model, the automated validation of internet security-sensitive protocols and applications (AVISPA) simulation tool, and heuristic informal security analysis, confirm that READ meets all 13 security evaluation criteria. Furthermore, compared to other seven advanced multi-factor user authentication schemes, READ excels in security and efficiency, making it ideal for practical multi-factor user authentication scenarios.

Design and feed two models for microstrip antenna in two different feed methods and compare their properties

In any wireless communication, the antenna plays a very important role. The need in this technology is to reduce the size of the antenna, weight, and cost with a low profile, high performance, and low return loss (RL), which is what researchers are striving for. This paper attempts to implement a rectangular microstrip patch antenna and analyze its performance for different types of feeding techniques. In this research, we designed two thin slice antennas fed in two different ways, using FR4 epoxy as an insulating substrate with a dielectric constant of 4.3. Copper was used as a conducting material for the radiating patch and the transmission line, with nearly similar geometrical dimensions. The first antenna has dimensions of (31x 26x1.6) m3 and the second antenna has dimensions of (30x27x1.6) m3. The first antenna operates with a coaxial probe feed technique and the second one operates with a microstrip line feed technique. The return loss for the first antenna we obtained is -26.0113dB with a standing wave voltage ratio of 1.1053 at a frequency of 3.59GHz, and -24.743GHz with a standing wave voltage ratio of 1.8908 at a frequency of 5.529GHz. The return loss for the second antenna is -27.468dB with a standing wave voltage ratio of 1.0884 at a frequency of 3.45GHz. The design, simulation, and inclusion of shapes and graphics for both antennas were done using the CST (Computer Simulation Tool) program

Research on the Design of Green Roofs for Office Buildings in Xuzhou Based on Building Energy Consumption Evaluation

The roof is the part of a building that is exposed to solar radiation for the longest period, making green roofs particularly effective in reducing air conditioning energy consumption during the summer. This study aims to assess the advantages of modular green roofs in terms of energy savings and cost reduction during the summer in Xuzhou. By conducting field measurements and surveys under both air-conditioned and non-air-conditioned conditions and utilizing building energy simulation tools, the performance of green roofs with different parameters was compared. Using EnergyPlus, factors such as soil thickness, thermal conductivity, and leaf area index were simulated. The results indicated that green roofs have superior thermal performance in summer, with the daily cooling load per unit area for top-floor rooms being 1.05 kWh/m2, 0.21 kWh/m2 lower than that for bare roofs, achieving an energy saving rate of 16.7%. It is recommended that soil thickness not exceed 0.3 m and insulation thickness not exceed 0.05 m or be set to 0 m. Take building no. 2 of the Xuzhou material market as an example: with the optimized green roof, the energy saving rate increased to 27.0%, which is 12.4% higher than that of the original green roof. The suggested cost for modular green roofs is 204 RMB/m2.

Perspectives on IoT-oriented network simulation systems

The Internet of Things (IoT) paradigm is assumed to be a major component in the present and future Internet, with forecasts claiming a humongous number of devices connected in the near future, and applications fields spanning from agriculture, to healthcare. Despite this, the standardization efforts have not yet resulted in widely adopted standards, and the market is fragmented into multiple solutions both at physical and communication protocol levels. Moreover, IoT systems exacerbate the usual test bed limitations, e.g., scalability (very large number of devices), hardware compatibility, space, and price. Due to the above problems, simulation tools become an extremely interesting tool for studying IoT systems both for academia (new algorithms), standardization (new protocols), and industry (what-if analysis). In this paper we will discuss what are the most relevant features and models that a simulation tool like ns-3 should prioritize to enable the above-mentioned needs from academia, standardization, and industry, and if they are achievable in the short, medium, or long term.

3D numerical modelling and laboratory study of flow field induced by a group of submerged vegetations

The three-dimensional (3D) numerical modelling in an open channel flow field of a group of submerged vegetations using computational fluid dynamics (CFD) platform of FLOW-3D HYDRO was performed in this study. A set of acoustic Doppler velocimetry (ADV) measurements have been conducted as benchmark to validate the numerical model. A quantitative comparison was performed on several hydrodynamic variables that impacted the vegetated open channel flow, such as flow depth, streamwise water velocity, turbulent intensity, and Reynolds shear stress. In the numerical analysis, the flow turbulence was treated using the RANS approach (within RNG k-ε); while the Volume Of Fluid (VOF) method was used to track the air-water interface. Structured meshes with hexahedral elements were used to discretize the channel geometry. In the findings, the numerical model reasonably reproduced the flow field and presented corresponding agreement with the experimental turbulent structures. This study showed that the differences in results between various analyses were all less than 10% and concludes that the presented numerical approach can be utilised as an efficient tool for simulations of the flow field within a vegetation patch (i.e. by using the simplified RANS approach).

Computational insights into the structural, thermodynamic and transport properties of CaF2-MgF2 binary fluoride system at high temperatures

The structural, thermodynamic and transport properties of the CaF2-MgF2 molten salt system were investigated with ab initio molecular dynamics (AIMD), system-specific neural network interatomic potentials (NNIPs) and universal PreFerred Potentials (PFP). We trained an NNIP model using AIMD data as input and used this potential to efficiently simulate the interactions within a large supercell in a temperature range of 1273–1773 K. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code was employed to validate our trained NNIP model. The Matlantis software with universal PFP is also presented to prove its feasibility for MD calculations and can be considered as a useful alternative simulation tool for higher-order systems where existing potentials are not readily available. We calculated structural and thermodynamic properties including radial distribution function (RDF), angular distribution function (ADF), specific heat capacity, ionic self-diffusivity, and viscosity. Our results indicate that the system exhibited a high degree of structural disorder, with the Ca, Mg, and F ions forming a liquid solution. Using PFP, the positions of the first peak in RDFs for Ca-F and Mg-F pairs are only slightly left-shifted (<0.05 Å), and the estimated viscosity of the melt decreases from 4.613 mPa·s to 1.846 mPa·s with an increase in temperature from 1273 K to 1773 K, in agreement with the NNIP trained specifically for CaF2-MgF2. Our results provide valuable insights into the properties of the CaF2-MgF2 system at high temperatures and serve as predictive models for the development of new electrolytes that could be used for silicon epitaxy by adding silica.

Scientific benchmarking: Engineering quality evaluation of electric vehicle concepts

We present a simulation tool that utilizes advanced modeling techniques to quantify the customer-relevant features of different battery electric vehicles (BEV) concepts. By incorporating comprehensive longitudinal and lateral dynamics analyses, the tool provides an in-depth understanding of passenger vehicle concepts in various driving conditions. Furthermore, the tool emphasizes evaluating comfort, presenting a holistic view concluding into the overall driving experience. Metrics considering the vehicle’s packaging are employed to assess the comfort aspects of the concepts. Implementing this simulation tool achieves a more systematic and reliable approach to evaluating BEV concepts. The application based on the parameters of 18 state-of-the-art BEV proved its compliance in the presented categories with the results of physical tests performed by reputable magazines with great experience and comprehensice test protocols. Its academic foundation ensures the utilization of state-of-the-art methodologies and the integration of the latest research findings in vehicle dynamics and comfort. This simulation tool offers automotive engineers, researchers, and industry stakeholders a valuable resource for objectively assessing and benchmarking the performance and comfort aspects of BEV concepts. With its ability to provide accurate evaluations and reasoning for weaknesses, this tool has the potential to significantly contribute to the advancement and optimization of future electric vehicle designs by assessing concepts in early development stages before physical prototypes are available, allowing for cost-efficient modifications.

Application of Numerical Modeling and Finite Element Analysis in Fused Filament Fabrication: A Review.

Additive manufacturing (AM) is not necessarily a new process but an advanced method for manufacturing complex three-dimensional (3D) parts. Among the several advantages of AM are the affordable cost, capability of building objects with complex structures for small-batch production, and raw material versatility. There are several sub-categories of AM, among which is fused filament fabrication (FFF), also commonly known as fused deposition modeling (FDM). FFF has been one of the most widely used additive manufacturing techniques due to its cost-efficiency, simplicity, and widespread availability. The FFF process is mainly used to create 3D parts made of thermoplastic polymers, and complex physical phenomena such as melt flow, heat transfer, solidification, crystallization, etc. are involved in the FFF process. Different techniques have been developed and employed to analyze these phenomena, including experimental, analytical, numerical, and finite element analysis (FEA). This study specifically aims to provide a comprehensive review of the developed numerical models and simulation tools used to analyze melt flow behavior, heat transfer, crystallization and solidification kinetics, structural analysis, and the material characterization of polymeric components in the FFF process. The strengths and weaknesses of these numerical models are discussed, simplifications and assumptions are highlighted, and an outlook on future work in the numerical modeling and FE simulation of FFF is provided.

Analysis of the performance of jacketed vessel using hybrid nanofluids in Aspen Plus

ABSTRACT Computer Simulation is used as an effective tool to analyse the performance of processes in industries. One such simulation tool, Aspen Plus, is used in this work to analyse the performance of a jacketed vessel along with the heat exchanger and pump for hybrid nanofluids. Hybrid nanofluids, are advanced fluids engineered by combining nanoparticles of different materials with base fluids like water, are introduced into the jacketed vessel with the primary objective of improving thermal management. The nanofluids are passed into the jacketed vessel to take away the heat of the fluid inside the vessel. The hot nanofluid coming out from the jacketed vessel is cooled using an air-cooled heat exchanger, and it is pumped again to the jacketed vessel. The performance of the jacketed vessel is compared with using water as a thermal fluid and the heat duty is found to be higher for nanofluids than water. The pressure drop and the velocity of the heat exchanger were also analysed for both hybrid nanofluids and water.

Factor of safety analysis for mine pillar considering the influence of the intermediate principal stress component

Failure of mine pillars, especially in deep underground mines, significantly threatens the safety of miners and equipment. Previous studies on mine pillar stability design have used classical constitutive models that ignore the intermediate principal stress component when determining the factor of safety. In this study, we develop and implement a three-dimensional modified Hoek–Brown (HB) constitutive model that incorporates the intermediate principal stress component into the numerical simulation tool FLAC3D. Furthermore, we propose and apply a strength-reduction technique to determine a more accurate factor of safety for mine pillars. This novel approach provides a more comprehensive and realistic method for geomechanical analysis and pillar design, enhancing our understanding of pillar stability. Through numerical analysis, we illustrate the impact of the intermediate principal stress component on mine pillar plasticity. The factor of safety is calculated via the strength reduction method, revealing a substantial improvement from 1.7 with the classical HB model to 2.0 with the 3D HB model. Including the intermediate principal stress component reduces the evolution of plasticity in the mine pillar. For instance, the volume of plastic zones diminishes, and the factor of safety increases as the width-to-height ratio increases. Exemplary simulations show that ignoring the effect of the intermediate principal stress component, including underestimating safety levels, designing suboptimal pillar design, and misinterpreting in situ observations and measurements, can lead to severe consequences.

Determining Payback Period and Comparing Two Small-Scale Vertical Axis Wind Turbines Installed at the Top of Residential Buildings

In recent years, residential buildings have seen a notable increase in energy consumption. To address this, it is crucial for researchers to invest in renewable energy technologies, aiming to develop highly sustainable and nearly-zero energy buildings. Many countries are started to commit to this goal, seeking to phase out fossil fuels due to their harmful environmental effects. Wind energy stands out as a promising renewable resource, especially in areas with strong wind patterns. This study focuses on a case in Karaburun, Izmir province, Türkiye, where annual wind speeds range from 6 to 8 m/s and evaluates the performance of two types of small-scale Vertical Axis Wind Turbines (VAWTs) in reducing energy consumption in a three-story residential building, along with associated costs. Utilizing advanced simulation tools like ANSYS Fluent and DesignBuilder Software, the study examines Ice-Wind VAWTs and Savonius VAWTs. The findings reveal that installing 15 Ice-Wind VAWTs on the building's roof can reduce energy consumption by approximately 22.5%, with each turbine costing about $2000 and a payback period of around 14.57 years. Conversely, using 15 Savonius VAWTs can reduce energy consumption by 36%, with each turbine costing about $2300 and a payback period of around 8.93 years. These results indicate that the Savonius turbine offers a faster return on investment compared to the Ice-Wind turbine under the specified conditions. Overall, this study highlights the significant benefits and cost implications of integrating renewable energy solutions like VAWTs into residential buildings.

Integrating terrestrial and non-terrestrial networks via IAB technology: System-level design and evaluation

As the telecommunications industry embarks on the transition to Sixth-Generation (6G) networks, this paper examines the integration of Non-Terrestrial Networks (NTN), and in particular satellite backhauling, in the context of Fifth-Generation (5G) systems. The Integrated Access and Backhaul (IAB) technology, conceived as a wireless terrestrial backhauling system in the Next Generation Radio Access Network (NG-RAN), has been identified as a possible enabler for the integration of satellite nodes. Despite the work already done in this direction, the combination of IAB architectures with satellite nodes operating in both the access and backhaul side requires further evaluations on feasibility and limitations for networks integrating Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellites. To this end, this work contributes providing insights on background technologies, as well as a detailed analysis of the issues and challenges arising from such integration and a definition of use cases to support narrow-band and broadband services. Furthermore, the design and implementation of a simulation tool is proposed for a performance evaluation in terms of registration time, link capacity, single-hop and end-to-end delay. Results show that the integration turns out to be feasible, even if with strong constraints coming from the satellite system rather than the IAB usage itself. Indeed, the earth-satellite link in LEO systems has a significant impact on the packet delivery time due to the discontinuous coverage. In case of GEO satellite instead, a non-terrestrial backhaul link could limit the performance of the whole system, especially at lower elevation angles.

Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison

Abstract. Uncertainty quantification (UQ) is a well-established category of methods to estimate the effect of parameter variations on a quantity of interest based on a solid mathematical foundation. In the wind energy field most UQ studies focus on the sensitivity of turbine loads. This article presents a framework, wrapped around a modern Python UQ library, to analyze the impact of uncertain turbine properties on aeroelastic stability. The UQ methodology applies a polynomial chaos expansion surrogate model. A comparison is made between different wind turbine simulation tools on the engineering model level (alaska/Wind, Bladed, HAWC2/HAWCStab2, and Simpack). Two case studies are used to demonstrate the effectiveness of the method to analyze the sensitivity of the aeroelastic damping of an unstable turbine mode to variations of structural blade cross-section parameters. The code-to-code comparison shows good agreement between the simulation tools for the reference model, but also significant differences in the sensitivities.

The Synergic Effect of Tubal Endometriosis and Women's Aging on Fallopian Tube Function: Insights from a 3D Mechanical Model.

The fallopian tubes are essential for human fertility, facilitating the movement of sperm and oocytes to the fertilization site and transporting fertilized oocytes to the uterus. Infertility can result from changes in the fallopian tubes due to tubal endometriosis and women's aging. In this study, we modeled human fallopian tubes with and without endometriosis for different women's age groups to evaluate the chances of normal sperm cells reaching the fertilization site and oocytes arriving at the uterine cavity. For this purpose, we employed a distinctive combination of simulation tools to develop a dynamic three-dimensional (3D) model of normal human sperm cells and oocytes swimming inside normal and endometriosis-affected human fallopian tubes for different women's group ages. We observed that in tubal endometriosis cases, fewer sperm cells reach the fertilization site and more oocytes become trapped in the tube walls compared to normal tubes. Additionally, aging decreases the number of sperm cells and oocytes reaching the fertilization site in normal and endometriosis-affected tubes. Our model evaluates the mechanisms of sperm and oocyte behaviors due to women's aging and fallopian tube issues caused by endometriosis, presenting new avenues for developing diagnostic and treatment tools for tubal endometriosis and age-related infertility issues.

Development of Detailed and Reduced Chemical Kinetic Models for Ammonia Gas Turbines

Abstract The power generation sector has been recently moving towards decarbonization and there is an increased interest in replacing conventional fossil fuels with fuels that produce reduced/zero carbon emissions. One such fuel is ammonia (NH3). However, ammonia is hard to ignite, has a low flame speed, and produces a significantly large amount of nitrogen oxide (NOx) emissions. Hence, using 100% ammonia as fuel in gas turbines requires significant modifications and the development of novel combustors. Blending hydrogen with ammonia, however, helps in having better control over the combustion properties. Before utilizing hydrogen-blended ammonia in an actual gas turbine combustor, thorough simulation studies are required to evaluate its performance, possible hazards, and emissions. The literature lacks well-validated chemical kinetic models for the combustion of hydrogen-blended ammonia for undiluted mixtures at gas turbine-relevant conditions (~20 bar). Hence, in this work, we develop a detailed chemical kinetic model for hydrogen blended ammonia combustion and validate it with a wide range of experimental data for both dilute and undiluted mixtures relevant to gas turbine operating conditions. The detailed chemical kinetic mechanism was reduced to a smaller version (32 species mechanism) without significant loss in accuracy using the direct relation graph with error propagation (DRGEP) and full species sensitivity analysis. The resultant mechanism can predict a wide range of experimental results with the least cumulative error and will be a valuable tool in CFD simulations that will enable the development of gas turbines for zero-carbon power generation.