High-fidelity Tools Research Articles

Enhanced Sensing of Diseased Blood Samples through One-Dimensional MgO-SiO2 Photonic Crystal Sensor

In this investigation, we present a tailored one-dimensional photonic crystal sensor (1D PCS), magnesium oxide (MgO) and silicon dioxide (SiO2) layers designed for the specific detection of diseased blood samples components, including plasma, platelets, red blood cells, and uric acid concentrations. The sensor structure is architecturally optimized for 6, 8,10,12,14, and 20 periods, encapsulating a central defect cavity that facilitates the interaction with the blood samples. Upon introducing the blood samples into this cavity, the transmittance spectrum is meticulously analyzed using the transfer matrix method to observe the variations in the defect mode’s wavelength. The study is conducted over a range of incident waves from wavelength 450 to 750 μm, enhancing the understanding of the sensor’s effect on the detection mechanism. In this context, our sensor demonstrates a remarkable sensitivity of approximately 815 nm per refractive index unit (RIU-1). It achieves a detection limit of 10–5, showcasing an exceptional ability to detect low concentrations of the infected blood components.Moreover, Q Factor of 3795 and FOM of 3369.18 indicate the sensor’s high precision in differentiating between healthy and infected blood samples.These findings underscore the potential of the proposed MgO-SiO2-based 1D PhC sensor in serving as a high-fidelity tool for biosensing application.

Plasticity analysis and a homogenized constitutive model of compressible multi-layer structure of battery

A homogenized constitutive model for the compressible multi-layer structure of battery (CMLSB) under external loading is essential for optimizing the structural design of electric assemblies. Currently, there is no specific constitutive model that is both mechanically explanatory and operationally applicable to CMLSB under varied loading conditions. In this study, due to limited understanding of the in-plane behavior of CMLSB, an analytical model was developed to investigate plasticity in this specific direction using the strain probing method. The observed plastic characteristics inspired the formulation of a novel two-dimensional constitutive framework for CMLSB in the in-plane direction.By integrating this new constitutive framework with one-dimensional plastic descriptions, a hybrid constitutive model was introduced and implemented in finite element software. Calibration and validation of the model were performed using a commercial pouch cell battery and its segments under various loading conditions. Finite element simulations with the hybrid model demonstrated remarkable accuracy in predicting the mechanical behavior of the cell under various in-plane and out-of-plane compression scenarios. Additionally, simulations were carried out to analyze the impact of cell packaging and air pressure. The new hybrid battery model is considered a user-friendly, physically interpretable, and high-fidelity tool, poised to significantly facilitate the comprehensive design of electric devices.

Multi-fidelity design framework integrating compositional kernels to facilitate early-stage design exploration of complex systems

Abstract Early-stage design of complex systems is considered by many to be one of the most critical design phases because that is where many of the major decisions are made. The design process typically starts with low-fidelity tools, such as simplified models and reference data, but these prove insufficient for novel designs, necessitating the introduction of high-fidelity tools. This challenge can be tackled through the incorporation of multi-fidelity models. The application of MF models in the context of design optimization problems represents a developing area of research. This study proposes incorporating compositional kernels into the autoregressive scheme (AR1) of Multi-Fidelity Gaussian Processes, aiming to enhance the predictive accuracy and reduce uncertainty in design space estimation. The effectiveness of this method is assessed by applying it to 5 benchmark problems and a simplified design scenario of a cantilever beam. The results demonstrate significant improvement in the prediction accuracy and a reduction in the prediction uncertainty. Additionally, the paper offers a critical reflection on scaling up the method and its applicability in early-stage design of complex engineering systems, providing valuable insights into its practical implementation and potential benefits.

Experimental and Computational Investigation of Aerodynamic Interactions in Quadrotor Configurations

The influence of interactional effects on quadrotor performance in forward flight was evaluated taking into account square and diamond configurations, forward and backward tilt angles, and a range of hub spacings including overlapping blades. The analysis was based on the wind-tunnel measurements and simulations from four midfidelity computational methods and the high-fidelity tool. The outcome indicates that the efficiency of a diamond configuration improves by 5% in comparison with isolated rotors for nonoverlapping rotor spacings, while the interactions in square alignments are detrimental for all analyzed test cases with the optimum at 0.04D blade overlap. The trend is more pronounced for the backward rotor tilt with intensified interactions, for which the efficiency of the diamond configuration increases by 11% at 1.2D rotor spacing. The computational results showed good agreement with the measurement data for the forward rotor plane tilt; however, for the backward tilt angle, the spread between the calculated values, especially for torque, could be observed with the general trends maintained. The study shows negligible impact of the rotor phasing on the quadrotor efficiency.

Validation of the dynamic simulation capabilities of Serpent2/Subchanflow using experimental data from the research reactor SPERT IV D-12/25

Research nuclear reactors are critical to the development of nuclear technology, but because of the complex configuration of the fuel assemblies and the different initial operating conditions, neutronic and thermal–hydraulic analyzes are performed with dedicated or adapted codes. These simulation tools might not be as accurate, since they use simple resolution methods and assumptions that do not always capture all aspects of the behavior of a nuclear research reactor. On the other hand, as time goes by, the evolution of numerical tools for the core analysis of power reactors have experienced a considerable progress. Nowadays, pin/subchannel level analysis of the core with coupled codes based on transport (SP3, MOC, SN, etc.) or Monte Carlo methods are applied in addition to the nodal diffusion codes. Hence, the research community is adapting and validating selected high-fidelity tools developed for power reactors to perform detail core analysis of e.g. Material Testing Reactors (MTR) cores at plate and subchannel level.This work deals with the validation of the high-fidelity coupled Serpent2/Subchanflow, which was modified and extended for the plate/subchannel analysis of MTR-cores, using the data of rod ejection tests performed in the SPERT IV D-12/25 reactor, especially the tests B-34 and B-35 were selected to validate the dynamic capability of Serpent2/Subchanflow. In these unique tests, experimental data e.g. thermal neutron flux, core power evolution during the rod ejection tests, and the plate cladding temperature was measured. It is noted that, due to the lack of detailed information on the initial conditions, the extraction and introduction scenarios of the transient rod for the reactivity insertion required calibrations and assumptions regarding velocity and position.The comparison of selected parameters predicted by the coupled simulations at plate/subchannel level of the SPERT IV reactor with the measured data at static and transient conditions shows excellent agreement confirming the high accuracy appropriateness of the used code for the analysis of research reactors. The calculated values of thermal neutron flux and core power evolution have a statistical error of ± 2 sigma. It was also found that the maximum temperature difference between calculated and experimental values is 7 °C and ∼ 10 °C for tests B-34 and B-35, respectively. In addition, the coupled code predicts for the first time the temperature of each plate and subchannel considering the local feedbacks between neutronics and thermal-hydraulics allowing the identification of the hottest/coldest plate in the core. The high-fidelity validation tool can provide comparison solutions for current research reactor core analysis methods, such as core analysis with point kinetics or 3D nodal diffusion codes coupled with fuel assembly-level thermal-hydraulics.

Successful Orthotopic Liver Transplantation in Mice Utilizing Microcomputed Tomography Angiography.

Microcomputed tomography (microCT) angiography is an invaluable resource to researchers. New advances in this technology have allowed for high-quality images to be obtained of micro-vasculature and are high-fidelity tools in the field of organ transplantation. In this model of orthotopic liver transplantation (OLT) in mice, microCT affords the opportunity to evaluate allograft anastomosis in real time and has the added benefit of not having to sacrifice study animals. The choice of contrast, as well as image acquisition settings, create a high-definition image, which gives researchers invaluable information. This allows for evaluation of the technical aspects of the procedure as well as potentially evaluating different therapeutics over an extended duration of time. In this protocol, we detail an OLT model in mice in a stepwise fashion and finally describe a microCT protocol that can give high-quality images, which aid researchers in in-depth analysis of solid organ transplantation. We provide a step-by-step guide for liver transplantation in a mouse, as well as briefly discuss a protocol for evaluating the patency of the graft through microCT angiography.

Multidisciplinary Design Optimization of Transonic Wings with Boundary-Layer Suction

A quasi-three-dimensional aerodynamic solver is developed for the aerodynamic analysis of wings in a transonic regime that is able to capture the effect of BLS in hybrid laminar flow control (HLFC) application or transition to turbulent flow for natural laminar flow (NLF). The tool provides accurate results, but without the high computational cost of high-fidelity tools. The solver combines the use of an Euler flow solver characterized by an integral boundary-layer method and linear stability analysis using a approximation for transition prediction. In particular, a conical transformation is adopted, including the determination of the shock-wave position. The solver is implemented in a multidisciplinary design optimization (MDO) framework, including wing weight estimation and aircraft performance analysis. The framework consists of different modules: aerodynamics, structure, suction system analysis, and performance evaluation. Using a genetic algorithm and considering HLFC technology, wing MDO has been performed to find the optimum wing planform and airfoil shape. A backward-swept wing (BSW) aircraft, developed inside the Cluster of Excellence–Sustainable and Energy Efficient Aviation (A) is studied. Novel technologies such as active flow control, limited maximum load factors due to load alleviation, and novel materials allow a fuel weight reduction of 6%.

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

Multidisciplinary structural optimization of novel high-aspect ratio composite aircraft wings

Novel high-aspect ratio airframe designs pave the way for a more sustainable aviation future. Such configurations enhance the aerodynamic efficiency of an aircraft through induced drag reduction mechanisms. Further performance gains, mainly in terms of structural mass, are accomplished via composite materials airframes. Nevertheless, undesired phenomena such as geometric nonlinearities and aeroelastic couplings due to elevated flexibility may often rise, rendering the design and optimization of such airframes extremely intricate and prohibitive in terms of computational cost. Low-fidelity tools, often preferred on the early design stages, accelerate the design process, albeit suffering from reduced accuracy and ability to capture higher-order phenomena. Contrastingly, high-fidelity computational methods incur excessive computational cost and are therefore utilized at the later, detailed design stages. There arises, therefore, the need for a combination of the various fidelities involved in a cost-effective manner, in order to drive the design towards optimal configurations without significant performance losses. In our approach, variable fidelity analyses are initially conducted in order to shed light on their effect on the structural response of a high-aspect ratio composite materials reference wing. An optimization framework combining low and high-fidelity tools in a sequential manner is then proposed, aiming at attaining a minimum mass configuration subject to multidisciplinary design constraints. As demonstrated, reasonable mass reduction was obtained for a future aircraft wing configuration.

Blade mass imbalance identification and estimation for three-bladed wind turbine rotor based on modal analysis

Early detection of rotor imbalance is one promising approach to address wind turbine durability. This work proposes a novel blade mass imbalance identification and estimation method for the wind turbine rotor. The method is capable of identifying the presence of a wind turbine rotor mass imbalance. In addition, if a mass imbalance exists in the wind turbine rotor, this method can identify which blade is imbalanced, and then quantify the imbalance severity. The remediation to balance the wind turbine rotor is also provided. The advantages of this method include that only a handful of data is required as input variables (which are the frequencies and modes shapes of all first-order modes) and the method can be applied to a stationary (non-rotating) rotor prior to the first operation. The decision-making process of this method is fast and reliable. The performance of the method is illustrated with the help of both numerical simulation and experimental tests. Model to test correlation and direct blade physical measurements are also conducted to validate the ability of the method to both identify mass imbalance and quantify the degree of mass imbalance. This method was demonstrated to be a high-fidelity tool for identifying the imbalance of the wind turbine rotor and it is also applicable to the wind turbines operating in the field. In addition, this method also shows strong potential to be extended to other wind turbine configurations and even other rotating machinery such as propellors and symmetric, repeated structures.

Finding Dangerous Waves—Review of Methods to Obtain Wave Impact Design Loads for Marine Structures

AbstractGreen water and slamming wave impacts can lead to severe damage or operability issues for marine structures. It is therefore essential to consider their probability and loads in design. This is difficult, as impacts are both hydrodynamically complex and relatively rare. The complexity requires high-fidelity modeling (experiments or CFD), whereas a statistically sound analysis of rare events requires long durations. High-fidelity tools are too demanding to run a Monte–Carlo simulation; low-fidelity tools do not include sufficient physical details. The use of extreme value theory and/or multi-fidelity modeling is therefore required. The present paper reviews the state-of-the-art methods to find wave impact design loads, which include response-conditioning methods, screening methods, and adaptive sampling methods. Their benefits and shortcomings are discussed, as well as challenges for the wave impact problem. One challenge is the role of wave non-linearity. Another is the validation of the different methods; it is hard to obtain long-duration high-fidelity wave impact data.

Investigations on the Potentials of Novel Technologies for Aircraft Fuel Burn Reduction through Aerostructural Optimisation

A physics-based optimisation framework is developed to investigate the potential advantages of novel technologies on the energy efficiency of a midrange passenger aircraft. In particular, the coupled-adjoint aerostructural analysis and optimisation tool FEMWET is modified to study the effects of active flow control at different load cases for conventional and unconventional wing configurations. This multidisciplinary design optimisation (MDO) framework presents the opportunity to optimise the wing considering static aeroelastic effect and, by its gradient-based method, save substantial computational time compared to high-fidelity tools, keeping a satisfying level of accuracy. Two different configurations are analysed: a forward- and backward-swept wing aircraft, developed inside the Cluster of Excellence SE2A (Sustainable and Energy-Efficient Aviation). The forward-swept configuration is sensitive to the aeroelastic stability effect, and the backward configuration is influenced by the aileron constraint. They may lead to a weight increment. Sensitivity studies show the possible role of key parameters on the optimisation results. The highest fuel weight reduction achievable for the two configurations is 5.6% for the forward-swept wing and 9.8% for the backward configuration. Finally, both optimised wings show higher flexibility.

A data-driven model-free adaptive controller with application to wind turbines

A data-driven controller is presented in this paper, which stems from the well known model-free adaptive control approach based on an equivalent linearized dynamical model of the plant. Inspired by the recent paper (Liu and Yang, 2019), the output tracking problem is here solved by a data-driven adaptive sliding-mode controller simultaneously ensuring prescribed performance constraints. To allow a rigorous stability analysis, the sliding variable, and the consequently derived controller, have been redesigned with respect to the inspiring paper. A proper setting of the gain of the discontinuous term is shown necessary to ensure closed loop stability. Validation of the technique has been extensively performed on the well assessed high-fidelity tool FAST (NREL) to solve the efficiency maximization problem using the proposed approach for a 5 MW wind turbine operating in the medium wind speed region.

Influence of lateral rotor spacing on the benefits in power generated by multi-rotor configurations

In this work, an analysis of the rotor wakes interaction for different array configurations of onshore wind turbines, has been made using CENER’s in-house aerodynamic module, called AeroVIEW. The study focuses on how the distance between rotors affects the increases in power and thrust obtained by configurations with more than one laterally aligned rotor. Two configurations of laterally aligned multi wind turbines of NREL 5-MW type, operating at 8 m/s wind speed and 9.21 rpm, have been analyzed. The first one consists of 5 wind turbines and the second one consists of 2 wind turbines. These configurations have been studied for different separation distances between the rotors hubs, between 1.1 diameters and 3 diameters. The increases obtained in power with AeroVIEW are in line to the results of high fidelity tools found in the literature. The results show a higher increment of power with lower separation distances. Moreover, this beneficial effect on the power generated, has a counterpart in the average thrust, whose increase is around half of the power increase.

Data-Driven system identification of 6-DoF ship motion in waves with neural networks

Critical evaluation of ship responses in the ocean is important for not only the design and engineering of future platforms but also the operation and safety of those that are currently deployed. Short-term temporal predictions of ship responses given the current wave environment and ship state would enable enhanced decision-making onboard and reduce the overall risk for both manned and unmanned vessels, especially as the marine industry trends towards more autonomy. However, state-of-the-art numerical hydrodynamic simulation tools are too computationally expensive to be employed for real-time ship motion forecasting. Thus, a methodology is needed to provide fast predictions with levels of accuracy closer to the higher-fidelity tools. A methodology is developed with long short-term memory (LSTM) neural networks to represent the motions of a free running David Taylor Model Basin (DTMB) 5415 destroyer operating at 20 knots in Sea State 7 stern-quartering long-crested irregular seas. Case studies are performed for both course-keeping and turning circle scenarios. An estimate of the vessel’s encounter frame is made with the trajectories observed in the training dataset. Wave elevation time histories are given by artificial wave probes that travel with the estimated encounter frame and serve as input into the neural network, while the output is the 6-DOF temporal ship motion response. Overall, the neural network is able to predict the temporal response of the ship due to unseen wave sequences accurately. The methodology, the dependence of model accuracy on wave probe and training data quantity and the estimated encounter frame are all detailed.

Ponderomotive force driven density modifications parallel to B on the LAPD

The ponderomotive force has previously been identified as a possible driver of observed density modifications close to radio frequency actuators during operation. This nonlinear force redistributes density in regions of gradients in the magnitude of an oscillating electric field and describes the influence of the fast time scale RF wave dynamics on slow time scale plasma transport. Depletion of the saturation current (a proxy for the density) measured at the Large Plasma Device (LAPD) was 30–35% during ion cyclotron range of frequencies operation. A coupled 1D plasma transport and cold plasma frequency domain wave solver was developed to self-consistently describe ponderomotive effects and was used to compare with results obtained from the LAPD experiment. The scaled current density driver for the wave model yielded an RF B field in close agreement with two components of the experimental data. However, the 1D parallel model did not accurately reproduce the amplitude or spatial distribution observed in experimental measurements of By. Within the limitations of the 1D model, initial simulation results showed that the ponderomotive force depleted up to 8% for high power (1 MW) and around 1% for the experimental power of 120 kW. This could suggest that the ponderomotive force is not the main driver of density modification for the LAPD experiments presented in this paper. Higher fidelity tools of at least 2D will be required to give a more realistic description of the RF E fields and the effect of the ponderomotive force on the LAPD.

High-Fidelity Steady-State and Transient Simulations of an MTR Research Reactor Using Serpent2/Subchanflow

In order to join efforts to develop high-fidelity multi-physics tools for research reactor analysis, the KIT is conducting studies to modify the coupled multi-physics codes developed for power reactors. The coupled system uses the Monte Carlo Serpent 2 code for neutron analysis and the Subchanflow code for thermo-hydraulic analysis. Serpent treats temperature dependence using the target motion sampling method and Subchanflow was previously extended and validated with experimental data for plate-type reactor analysis. This work present for the first time the steady-state and transient neutron and thermo-hydraulic analysis of an MTR core defined in the IAEA 10 MW benchmark using Serpent2/Subchanflow. Important global and local parameters for nominal steady-state conditions were obtained, e.g., the lowest and highest core plate/channel power/temperature, the radial and axial core power profile at the plate level, and the core coolant temperature distribution at the subchannel level. The capabilities of Serpent2/Subchanflow to perform transient analysis with on-the-fly motion of the control plates were tested, namely with fast and slow reactivity insertion. Based on the unique results obtained for the first time at the subchannel and plate level, it can be stated that the coupled Serpent2/Subchanflow code is a very promising tool for research reactor safety-related investigations.

On the Incipient Indicial Lift of Thin Wings in Subsonic Flow: Acoustic Wave Theory with Unsteady Three-Dimensional Effects

Enhanced approximate expressions for the incipient indicial lift of thin wings in subsonic potential flow are presented in this study, featuring explicit analytical corrections for the unsteady downwash. Lifting-line and acoustic-wave theories form the basis of the method, within an effective synthesis of the governing physics, which grants a consistent generalised framework and unifies previous works. The unsteady flow perturbation consists of a step-change in angle of attack or a vertical sharp-edged gust. The proposed model is successfully evaluated against numerical results in the literature for the initial airload development of elliptical and rectangular wings with a symmetric aerofoil, considering several aspect ratios and Mach numbers. While nonlinear downwash and compressibility terms demonstrate marginal (especially for the case of a travelling gust), both linear and nonlinear geometrical effects from a significant taper ratio, sweep angle or curved leading-edge are found to be more important than linear downwash corrections (which are crucial for the circulation growth at later times instead, along with linear compressibility corrections). The present formulae may then be used as a rigorous reduced-order model for validating higher-fidelity tools and complex simulations in industrial practice, as well as for estimating parametric sensitivities of unsteady aerodynamic loads within the preliminary design of aircraft wings in the subsonic regime.

Assessment of the Influence of Added Resistance on Ship Pollutant Emissions and Freight Throughput Using High-Fidelity Numerical Tools

The reduction of ship pollutants is a key issue in the international agenda. Emissions estimation is usually based on standard calculations that consider the different scenarios of ships. This work presents research on the influence of added resistance on ship emissions and freight throughput. First, a methodology to assess the added resistance influence is shown. The procedure is applied to a roll on-roll off ship under two load conditions. Analyses are computed to value wind- and wave-added resistances for different seasons. An investigation on ship pollutant emissions for a whole route is performed. Moreover, the influence of added resistance on the ship freight throughput is analyzed. Finally, some relevant information is concluded. For instance, a difference of up to 53% in pollutant emission estimation is observed if added resistance is considered. Additionally, the navigation in added resistance conditions could lead to a freight loss of 18% per operational year.

Machine learning-assisted surrogate construction for full-core fuel performance analysis

Accurately predicting the behavior of a nuclear reactor requires multiphysics simulation of coupled neutronics, thermal-hydraulics and fuel thermo-mechanics. Traditionally, fuel performance analysis is performed standalone as result of the cost induced by the full-core analysis. This work is therefore motivated to improve the computational efficiency of full-core modeling by constructing fast-running surrogate for fuel performance quantities of interest using machine learning. Rule-based models are used to account for the spatial–temporal-dependent operating histories, and expanded space-filling design is employed to ensure the appropriateness of the training set. Proposed methodologies are verified on both standard and high burnup PWR cores, achieving at least ten thousand times acceleration compared to FRAPCON with satisfying prediction accuracy. Current work lays foundation for tighter coupling of the fuel performance analysis into the core design optimization framework. It also sets stage for full-core fuel performance analysis with high-fidelity tools like BISON whose computational cost is more burdensome.