Multi-physics Approach Research Articles

The Development of a Multiphysics Coupled Solver for Studying the Effect of Dynamic Heterogeneous Configuration on Particulate Debris Bed Criticality and Cooling Characteristics

For a sodium-cooled fast reactor, the capability for stable cooling and avoiding re-criticality on the debris bed is essential for achieving in-vessel retention when severe accidents occur. However, an unexploited uncertainty still existed regarding the compound effect of the heterogeneous configuration and dynamic particle redistribution for the debris bed’s criticality and cooling safety assessment. Therefore, this research aims to develop a numerical tool for investigating the effects of the different transformations of the heterogeneous configurations on the debris bed’s criticality/cooling assessment. Based on the newly proposed methodology in this research, via integrating the Discrete Element Method (DEM) with Computational Fluid Dynamics (CFD) and Monte-Carlo-based Neutronics (MCN), the coupled CFD–DEM–MCN solver was constructed with the originally created interface to integrate two existing codes. The effects of the different bed configurations’ transformations on the bed safety assessments were also quantitively confirmed, indicating that the effect of the particle-centralized fissile material had the dominant negative effect on the safety margin of avoiding re-criticality and particle re-melting accidents and had a more evident impact than the net bed-centralized effect. This coupled solver can serve to further assess the debris bed’s safety via a multi-physics simulation approach, leading to safer SFR design concepts.

Assessing the coastal hazard of Medicane Ianos through ensemble modelling

Abstract. On 18 September 2020, Medicane Ianos hit the western coast of Greece, resulting in flooding and severe damage at several coastal locations. In this work, we aim at evaluating its impact on sea conditions and the associated uncertainty through the use of an ensemble of numerical simulations. We applied a coupled wave–current model to an unstructured mesh, representing the whole Mediterranean Sea, with a grid resolution increasing in the Ionian Sea along the cyclone path and the landfall area. To investigate the uncertainty in modelling sea levels and waves for such an intense event, we performed an ensemble of ocean simulations using several coarse (10 km) and high-resolution (2 km) meteorological forcings from different mesoscale models. The performance of the ocean and wave models was evaluated against observations retrieved from fixed monitoring stations and satellites. All model runs emphasized the occurrence of severe sea conditions along the cyclone path and at the coast. Due to the rugged and complex coastline, extreme sea levels are localized at specific coastal sites. However, numerical results show a large spread of the simulated sea conditions for both the sea level and waves, highlighting the large uncertainty in simulating this kind of extreme event. The multi-model and multi-physics approach allows us to assess how the uncertainty propagates from meteorological to ocean variables and the subsequent coastal impact. The ensemble mean and standard deviation were combined to prove the hazard scenarios of the potential impact of such an extreme event to be used in a flood risk management plan.

Depletion-driven thermochemistry of molten salt reactors: review, method, and analysis

Molten salt reactors (MSRs) are innovative advanced nuclear reactors that utilize nuclear fuel by dissolving it in a high-temperature liquid salt. This unique feature differentiates MSRs from other types of reactors and allows for enhanced safety and economic performance. The liquid fuel also entails several multiphysics effects that can complicate reactor design and operation. One primary effect termed here as depletion-driven thermochemistry is a driving force in altering the multiphysics behavior of the reactor. Essentially, depletion-driven thermochemistry is the effect that fuel depletion has on changing the chemical redox potential of the fuel salt over time. As the fuel is consumed, the redox potential shifts toward a more oxidizing state. Without active control, the changing chemistry due to depletion increases corrosion thereby limiting reactor component lifetimes. Additionally, the changing redox potential of the fuel salt alters the vapor pressures of chemical species dissolved in the fuel salt. Changing vapor pressures of species in the fuel salt is an important parameter to understand when off-gassing volatile species during normal reactor operation, and for source term characterization during accident scenario transients. The present work represents a fundamental step toward modeling and coupling the driving physics (i.e., neutronics and chemistry) involved in altering the redox potential in an MSR. Here, the neutronic code Griffin models the depletion of the fuel-salt system, while the chemical equilibrium code Thermochimica calculates the thermochemical state of the isotopic inventory, using the Molten Salt Thermodynamic Database - Thermochemical (MSTDB-TC). These two codes are tightly coupled to predict the impact of fuel depletion in altering the chemistry in MSR systems. Redox potential control methods are discussed and can be modeled using this multiphysics approach. The vapor pressures of chemical species that could be extracted to an off-gas system, as determined by the reactor’s thermochemical state, are examined. The neutronics-chemistry coupling developed in this work is expected to have potential application for analyzing corrosion, source term evolution, and material safeguards in MSR systems. Lastly, suggestions for areas of further improvements of the models to expand these capabilities by incorporating other coupled physics effects is provided.

COMPARISON BETWEEN EXPERIMENTATION AND MULTIPHYSICS MODELLING TO IDENTIFY PRIORITY CONTRADICTION

AbstractThe contradictions of TRIZ are now widespread and recognized as an effective inventive design tool. They make it possible to find solution concepts to problems that cannot be solved by optimization approaches. However, many contradictions could be formulated and it could be difficult to choose the priority one. The authors propose here two methods to formulate the contradictions and identify the priority contradiction: an experimental approach on the one hand, and a multiphysics approach on the other hand. This analysis, illustrated through an example of 3D printing of parts, shows that these two approaches are similar in terms of result, and indeed make it possible to formulate contradictions taking into account all the complexity of a system.

Multiphysics Interaction Analysis of the Therapeutic Effects of the Sigmoid Sinus Wall Reconstruction in Patients with Venous Pulsatile Tinnitus.

Sigmoid sinus wall dehiscence (SSWD) is an important etiology of venous pulsatile tinnitus (VPT) and is treated by sigmoid sinus wall reconstruction (SSWR). This study aimed to investigate the therapeutic effects of the different degrees of SSWR and the prognostic effect in patients with VPT. Personalized models of three patients with SSWD (control), 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD were reconstructed. A multiphysics interaction approach was applied to elucidate the biomechanical and acoustic changes. Results revealed that after SSWR, the average pressure of venous vessel on the SSWD region reduced by 33.70 ± 12.53%, 35.86 ± 12.39%, and 39.70 ± 12.45% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, and 1/4SSWD. The maximum displacement of the SSWR region reduced by 25.91 ± 30.20%, 37.20 ± 31.47%, 52.60 ± 34.66%, and 79.35 ± 18.13% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD, with a magnitude approximately 10-3 times that of the venous vessel in the SSWD region. The sound pressure level at the tympanum reduced by 23.72 ± 1.91%, 31.03 ± 14.40%, 45.62 ± 19.11%, and 128.46 ± 15.46% (mean ± SD). The SSWR region was still loaded with high stress in comparison to the surrounding region. The SSWR region of the temporal bone effectively shielded the high wall pressure and blocked the transmission of venous vessel vibration to the inner ear. Patients with inadequate SSWR still had residual VPT symptoms despite the remission of VPT symptoms. Complete SSWR could completely solve VPT issues. High-stress distribution of the SSWR region may be the cause of the recurrence of VPT symptoms.

Geometric modifications to bluff body for enhanced performance in a wind-induced vibration energy harvester

Specialized sensors in wireless networks monitor the environment with minimal power, which is typically provided by batteries but it can also be powered with renewable sources using smart materials. One such solution is piezoelectric wind energy harvesting to power these sensors. However, the low output power of piezoelectric materials is still a concern. This research aims to improve piezoelectric wind energy harvesting by modifying the geometry of the bluff body. A square-shaped bluff body is used as a reference, and geometric changes are made by attaching square-shaped extensions. The study creates a mathematical model of a cantilever beam system with a piezoelectric material at fix end and a bluff body at the free end, using a multi-physics approach that combines electromechanical and aerodynamic models. The study uses MATLAB Simulink to solve the differential equations and verify the results with experiments. A parametric analysis examines the impact of external resistance, wind speed, and bluff body shape on circuit metrics. The study found that at a wind speed of 6 m/s and an optimal load resistance of 200 kΩ, the system generated 4.984 mW of power. This result demonstrates the potential of wind energy harvesting to power various distributed sensors for a wide range of applications.

Effect of geometrical defects on the acoustical and transport properties of periodic porous absorbers manufactured using stereolithography

Additive manufacturing allows the fabrication of acoustical materials with previously unrealizable micro- and macrostructural complexities. However, the still nascent understanding of various geometrical defects occurring during the additive process remains a barrier to accurately predicting the acoustical behavior of such complex absorbers. In this study, we present the results from our efforts on numerically modeling the absorption behavior of periodic porous absorbers fabricated using the stereolithography (SLA) technique using the hybrid micro-macro multiphysics approach. Specifically, we focus on understanding the role played by the expansion or shrinkage of the solid ligaments during the SLA process on the transport parameters of the final printed samples. First, the periodic absorbers are modeled using COMSOL multiphysics, where the transport properties are derived using the Johnson-Champoux-Allard-Lafarge-Pride (JCALP) semiempirical model. Results from the parametric study guide the design and fabrication of test articles that closely match the initial design requirements. Finally, the fabricated samples are tested using an impedance tube, and the obtained absorption properties are compared to the a priori numerical predictions. Results indicate that accounting for fabrication defects within the numerical modeling schema can provide reliable sound absorption predictions for additively manufactured porous absorbers.

Modeling the radiative, thermal and chemical microenvironment of 3D scanned corals

Reef building corals are efficient biological collectors of solar radiation and consist of a thin stratified tissue layer spread over a light scattering calcium carbonate skeleton surface that together construct complex three dimensional (3D) colony structures forming the foundation of coral reefs. They exhibit a vast diversity of structural forms to maximize photosynthesis of their dinoflagellate endosymbionts (Symbiodiniaceae), while simultaneously minimizing photodamage, offer resistance to hydrodynamic stress, reduce attack by predators and increase prey capture and heterotrophic feeding. The symbiosis takes place in the presence of dynamic gradients of light, temperature and chemical species that are affected by the interaction of incident irradiance and water flow with the coral colony. We developed a multiphysics modelling approach to simulate the microscale spatial distribution of light, temperature and O2 in a coral fragment with its morphology determined by 3D scanning techniques. Model results compared well with spatial measurements of light, O2 and temperature under similar flow and light conditions. The model enabled us to infer the effect of coral morphology and light scattering in tissue and skeleton on the internal light environment experienced by the endosymbionts, as well as the combined contribution of light, water flow and ciliary movement on O2 and temperature distributions in the coral.

Dynamic Modeling of a Pressurized Alkaline Water Electrolyzer: A Multiphysics Approach

In this paper a dynamic model for the simulation of pressurized alkaline water electrolyzers is presented. The model has been developed following a multiphysics approach, integrating electrochemical, thermodynamic, heat transfer and gas evolution processes in order to faithfully reproduce the complete dynamical behavior of these systems. The model has been implemented on MATLAB/Simulink and validated through experimental data from a 1 Nm3/h commercial alkaline water electrolyzer. Validations have been performed under real scenarios where the electrolyzer is working with power profiles characteristic from renewable sources, wind and photovoltaic. The simulated results have been found to be consistent with the real measured values. This model has a great potential to predict the behavior of alkaline water electrolyzers coupled with renewable energy sources, making it a very useful tool for designing efficient green hydrogen production systems.

Multiphysics Modeling of Plasmon-Enhanced All-Optical Helicity-Dependent Switching.

In this work, we propose a multiphysics approach to simulate all-optical helicity-dependent switching induced by the local hot spots of plasmonic nanostructures. Due to the plasmonic resonance of an array of gold nanodisks, strong electromagnetic fields are generated within the magnetic recording media underneath the gold nanodisks. We construct a multiphysics framework considering the opto-magnetic and opto-thermal effects, and then model the magnetization switching using the Monte Carlo method. Our approach bridges the gap between plasmonic nanostructure design and magnetization switching modeling, allowing for the simulation of helicity-dependent, nanoscale magnetization switching in the presence of localized surface plasmons.

Continuous flow hydrothermal synthesis of zeolite LTA in intensified reactor. Experimental and multiphysics CFD modeling approach

Zeolites are conventionally synthesized in batch-wise hydrothermal processes that usually take several hours or days to complete. In current research work, continuous flow process is developed on pilot scale for the hydrothermal synthesis of zeolite LTA. The pilot reactor was able to produce highly crystalline zeolite nanoparticles without any clogging, which often encounters for particle flow in tubular reactors. Steady-state zeolite production rates of 55–80 g⋅h −1 (dry basis) were achieved with a residence time below 10 min, with corresponding space time yields (STY) between ca. 700 and 1100 g⋅L −1⋅h −1. A couple CFD model with a population balance model was developed to investigate the continuous flow hydrothermal process. The average particle size obtained from the model was in good agreement with the experimental data. The model was further applied to study the effects of critical parameters, such as temperature and flow rate, to highlight potential process optimization directions.

A novel high-dimensional and multi-physics modeling approach of proton exchange membrane fuel cell for real-time simulation

Fuel cell model provides state observation and quantitative analysis for Hardware-In-the-Loop (HIL) test platform. For a high-dimensional multi-physics model, the observed distribution of physical properties is meaningful for fuel cell stack optimization, manufacturing process and model-based control development. However, traditional modeling approach is difficult to consider both the calculation accuracy and efficiency. To solve this problem, this paper proposes a high-dimensional multi-physics real-time modeling approach for fuel cells based on partial differential equations (PDEs)-tridiagonal matrix equation transformation (TMET) and symmetric successive overrelaxation (SSOR) algorithm. In the proposed method, a generalized framework of TMET and a novel staggered grid technique is developed. In this case, both the convection and diffusion phenomena can be accurately described. For different fuel cells or parameters change, supplementary model modification or development is not required, only the global variables need to be re-assigned. Moreover, SSOR with bi-directional iteration mechanism is used to increase the probability of computational convergence and thus improve the calculation efficiency. Compared with commercial COMSOL model, by using the proposed modeling approach, the mean absolute percentage error (MAPE) of the simulated polarization output characteristics is 1.77%, the MAPE of different distribution characteristics can remain within 10%, and the calculation time can be shortened from hours even days to seconds.

A mechanobiological model for tumor spheroid evolution with application to glioblastoma: A continuum multiphysics approach

Background:Spheroids are in vitro quasi-spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanisms, the effect of gradients of nutrients, or the creation of realistic 3D biological structures. The main objective of this work is to link the spheroid evolution with the mechanical activity of cells, coupled with nutrient consumption and the subsequent cell dynamics. Method:We propose a continuum mechanobiological model which accounts for the most relevant phenomena that take place in tumor spheroid evolution under in vitro suspension, namely, nutrient diffusion in the spheroid, kinetics of cellular growth and death, and mechanical interactions among the cells. The model is qualitatively validated, after calibration of the model parameters, versus in vitro experiments of spheroids of different glioblastoma cell lines. Results:Our model is able to explain in a novel way quite different setups, such as spheroid growth (up to six times the initial configuration for U-87 MG cell line) or shrinking (almost half of the initial configuration for U-251 MG cell line); as the result of the mechanical interplay of cells driven by cellular evolution. Conclusions:Glioblastoma tumor spheroid evolution is driven by mechanical interactions of the cell aggregate and the dynamical evolution of the cell population. All this information can be used to further investigate mechanistic effects in the evolution of tumors and their role in cancer disease.

Thermo4PFM: Facilitating Phase-field simulations of alloys with thermodynamic driving forces

Phase-field modeling is a popular front-tracking approach used to model solidification. Its time-evolution equations are often coupled to alloy composition and/or thermal diffusion in high-resolution multiphysics approaches. Materials thermodynamic properties tabulated in CALPHAD databases can be used for phase-field modeling to parameterize bulk energies of alloys. In addition, they can be naturally integrated into models such as the Kim-Kim-Suzuki (KKS) model where driving forces depend on the differences between chemical potentials of co-existing phases. In that case, a small system of coupled nonlinear equations needs to be solved at every point in space where the phase-field order parameter is to be updated and evolved in time. We present Thermo4PFM, a solver for the KKS equations for binary and ternary alloys, with two or three phases, and parameterized with CALPHAD models. Thermo4PFM is open source, written in C++, and can take advantage of Graphics Processing Units (GPU) accelerators. Using OpenMP offload capabilities for C++ classes, an excellent performance is demonstrated on GPU using the LLVM compiler. CALPHAD data is read from simple JSON files using an open source parser from the boost library. Program summaryProgram Title: Thermo4PFMCPC Library link to program files:https://doi.org/10.17632/8j3ntp5c7k.1Developer's repository link:https://github.com/ORNL/Thermo4PFMLicensing provisions: BSD 3-clauseProgramming language: C++/OpenMPNature of problem: Accurate modeling of solidification in metallic alloys requires thermodynamic data associated with possible material phases. That data can be used in phase-field modeling (PFM) to evaluate the driving force responsible for phase changes and solidification front motion. Integrating that data into PFM requires the solution of a small system of coupled nonlinear differential equations — the Kim-Kim-Suzuki equations — that needs to be solved at every point of a discretization mesh.Solution method: Thermo4PFM implements a Newton-based solver for the Kim-Kim-Suzuki equations for a few special cases (binary and ternary alloys with two or three phases) for CALPHAD-based models of the bulk energy of the phases. The software is written in C++ and uses the Curiously Recurring Template Pattern and OpenMP offload capabilities to take advantage of GPU accelerators, when available, on modern High Performance Computing resources. It also uses the boost Property Tree library to parse input CALPHAD data.

CFD analysis of the hyper-viscous effects on blood flow across abdominal aortic aneurysm in COVID patients: multiphysics approach

Recent research has shown that individuals suffering from COVID-19 are accommodating an elevated level of blood viscosity due to the morphological changes in blood cells. As viscosity is a major flow parameter influencing the flow across a stenosis or an aneurysm, the examination of the significance of hyperviscosity in COVID patients is imperative in arterial pathologies. In this research, we have considered a patient-specific case in which the aneurysm is located along the abdominal aortal walls. Recent research on the side effects of COVID-19 voiced out the various effects on the circulatory system of humans. Also, as abdominal aneurysms exist very often among individuals, causing the death of 150–200 million every year, the hyper-viscous effects of blood on the flow across the diseased aorta are explored by considering the elevated viscosity levels. In vitro explorations contribute considerably to the clinical methods and treatments to be regarded. The objective of the present inquest is to research the flow field in aneurysmatic-COVID-affected patients considering the elastic nature of vessel walls, using the arbitrary Lagrangian-Eulerian approach. The study supports the various clinical findings that voiced the detrimental effects associated with blood hyperviscosity. The simulation results obtained, by solving the fluid mechanics’ equations coupled with the solid mechanics’ equations, employing a FEM solver suggest that the elevated stress imparted by the hyper-viscous flows on the walls of the aneurysmal aorta can trigger the fastening of the aneurysmal sac enlargement or rupture.

Both network architecture and micro cracks effects on lacuno-canalicular liquid flow efficiency within the context of multiphysics approach for bone remodeling

When physical forces are applied to bone, its mechanical adaptive behaviors change according to the microarchitecture configuration. This leads to changes in biological and physical thresholds in the remodeling cell population, involving sensor cells (osteocytes) interacting with each other and changes in osteocyte shape due to variation in lacunar shape. The resulting alterations in fluid flow leads to changes in the membrane electrical potential and shear stress. Eventual creation of microcracks, may lead in turn to modify cell activity. In contrast, the redundancy in the lacuno canalicular network (LCN) interconnectivity maintains partial flow. Our goal was to investigate the role of fluid flow in LCN by proposing a model of electro-mechanical energy spread through inhomogeneous microarchitectures. We focused on mechano-sensitivity to changes in load-induced flow impacted by neighboring micro cracks and quantifying its critical role in changing, velocity, shear stress and orientation of liquid mass transportation from one cell to another. To enhance the concept of intricacy LCN micro-structure to fluid flow, we provide a new combined effects factor considered as osteocytes sensor efficiency. We customized an influence function for each osteocyte, coupling: in one hand, the spatial distribution within remodeling influence areas, conducting a significant fluid spread, leading hydro-dynamic behavior and impacted further by presence of micro cracks and; in other hand, the fluid electro kinetic behavior.As an attempt to fill the limitations stated by many of the recent studies, we reveal in numerical simulation, some results which cannot be measured in vitro/in vivo studies. Numerical calculations were performed in order to evaluate, among many others, how liquid flow conditions changes between lacunas, how the orientation and the magnitude of the governing flow in LCN can regulate osteocytes efficiency. In addition to be regulated by osteocytes, a direct effects of fluid flow are also acting on osteoblast activity. In summary, this new approach considers mechano-sensitivity in relation to liquid flow dynamic and suggests additional pathway for Osseo integration via osteoblast regulation. However, this novel modeling approach may help improve the mapping and design bone scaffolds and/or selection of scaffold implantation regions.

Multi-physics coupled simulation on steady-state and transients of heat pipe cooled reactor system

With superior inherent safety and low maintenance demand, heat pipe cooled micro-reactor is a potential solution for decentralized remote electricity supply, as well as space power technology. Multi-physics coupled analysis is important to evaluate the inherent safety feature of micro-reactor. However, in the existing multi-physics coupling simulations, lumped parameter core heat transfer model and low-fidelity heat pipe model cannot accurately predict steady-state and transient safety margin of the reactor. In order to improve the simulation accuracy, a standalone two-dimensional transient high-temperature heat pipe analysis code was developed and validated. The heat pipe analysis code was coupled with the three-dimensional thermal conduction calculation of reactor core, as well as the point reactor kinetics, the alkali metal thermal-to-electric converter model and the heat pipe radiator model, to realize fully coupled analysis of reactor system. With the power distribution in the reactor core, the steady state, startup transient and single heat pipe failure accident were simulated based on the multi-physics coupling. The steady-state simulation results show that the heat flux of heat pipes shows significant non-uniformity in both circumferential and axial directions. The peak heat flux (120 kW/m2), with the twice value of averaged one (60 kW/m2), occurs on the heat pipes near the reactor edge rather than in the center. During reactor startup, the reactivity-insertion rate of 1.67e-3 $/s increases the transient peak heat flux to 260 kW/m2. The isothermal feature of heat pipes results in inverse heat transfer, i.e. from heat pipes to reactor structure, which improves the axial and radial reactor heat transfer and flattens the reactor temperature distribution. In the central heat pipe failure accident, more severe local temperature rise was observed in the core structure than that in the fuel pins. The peak heat flux location is shifted to the heat pipes adjacent to the failed heat pipe. Benefitted from the developed high-fidelity multi-physics coupling approach, the realistic transient phenomena in heat pipe cooled micro-reactor could be revealed.

Advancing OHL Rating Calculations: Modeling Mixed-Convective Cooling and Conductor Geometry

The existing standard current-temperature calculations for overhead line (OHL) conductors have been adequate for conventional conductors and their operating temperatures. However, these calculations make assumptions and include simplifications about conductor geometry and aero-thermal-dynamics, introducing an error in the High-Temperature Low-Sag conductors operating temperatures. To quantify the error introduced by the shape of strands, the paper employs a Multi-Physics Finite Element Modeling approach that calculates the conjugate heat transfer for trapezoidal stranded OHL conductors. Furthermore, it proposes corrective equations to improve the accuracy of existing methods. The equations incorporate a new Nusselt number correlation for mixed convection and capture the surface area ignored by current calculations. The outer conductor geometry assumptions and the combined natural and forced convective cooling omission in the IEEE and CIGRE methods introduce an error at low (below 0.12 m/s) cross-flow wind speeds suggesting an underestimation of conductor temperature by up to 4%. In medium wind speeds, typically at 0.5 m/s–0.61 m/s, the standard methods overestimate the conductor temperature limiting its current-carrying capability. A 5% uprating for existing OHLs is potentially feasible, particularly for the trapezoidal stranded conductors, when removing the assumptions made in existing methods.

Advances in material phase change modelling approach for EU-DEMO limiter’s plasma-facing components

Within the EU-DEMO first wall protection framework, work on limiter’s plasma-facing component design has started under plasma disruptive events (Richiusa et al., 2022). Starting from the rationale behind the TARTIFL&TTE software (Richiusa et al., 2022), this companion paper describes the progress on the engineering modelling of the plasma-facing material phase change under high heat flux, with the aid of COMSOL Multiphysics® software. The aim is to develop a reliable technique which can be used by designers for predicting how much of the solid armour undergoes phase change. This helps satisfy requirements for actively cooled components, such as at which armour depth safely locating the cooling system, and if its design can safely handle the heat transfer in the resulting component configuration after the disruption is extinguished. A few changes to the driving idea in Richiusa et al. (2022) will be also highlighted.The multiphysics software allows us to implement a 1D model which can be extended to 2D/3D geometries subjected to both uniform and non-uniform heat flux. It also offers the capability of conjugated heat transfer in solids and liquids by coupling the two different domains. Although this multiphysics approach is also investigated, no effort in melting layer motion modelling is done. Therefore, the equivalent way of validating this approach while reducing its computational time is working with one single solid domain, within which any liquid phase changes are tracked by an apparent heat capacity formulation. The vapour domain is not modelled. The material removal due to the evaporative mass flux is modelled by means of moving mesh frames which push the recessing liquid interface backwards according to gas kinetics-driven boundary conditions. The melt pool is not removed during the transient. Mass balance considerations drive the liquid-to-vapour interface velocity.The 3D Multiphisics implementation (3D-TARTIFL&TTE), is here supported by a benchmark activity and an application to the limiter’s plasma-facing armour, whose preferred chosen thickness is 20 mm.

A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers

Nanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to enhance light-matter interactions. Despite these breakthroughs, design, fabrication, and characterization of such exotic devices have remained through iterative processes which are often computationally costly, memory-intensive, and time-consuming. In contrast, deep learning approaches have recently shown excellent performance as practical computational tools, providing an alternate avenue for speeding up such nanophotonics simulations. This study presents a DNN framework for transmission, reflection, and absorption spectra predictions by grasping the hidden correlation between the independent nanostructure properties and their corresponding optical responses. The proposed DNN framework is shown to require a sufficient amount of training data to achieve an accurate approximation of the optical performance derived from computational models. The fully trained framework can outperform a traditional EM solution using on the COMSOL Multiphysics approach in terms of computational cost by three orders of magnitude. Furthermore, employing deep learning methodologies, the proposed DNN framework makes an effort to optimise design elements that influence the geometrical dimensions of the nanostructure, offering insight into the universal transmission, reflection, and absorption spectra predictions at the nanoscale. This paradigm improves the viability of complicated nanostructure design and analysis, and it has a lot of potential applications involving exotic light-matter interactions between nanostructures and electromagnetic fields. In terms of computational times, the designed algorithm is more than 700 times faster as compared to conventional FEM method (when manual meshing is used). Hence, this approach paves the way for fast yet universal methods for the characterization and analysis of the optical response of nanophotonic systems.