Grid Nodes Research Articles

Проектирование силовых конструкций с использованием топологической оптимизации и технологии аддитивного производства

The aim of the work is to create an integrated technology for designing load-bearing structures using topological optimization and additive manufacturing, as well as its approbation on the example of a specific task of designing and manufacturing an aerospace structure. The proposed methodology describes the main design stages for additive manufacturing. In the ANSYS system, the power scheme of the structure is designed based on topological optimization. To refine the dimensions and shape of the structural strength elements, a module was used that allows optimizing the geometric model of the structure by shifting the nodes of the design grid of the structure. The results of the verification calculation showed that the designed structure has a significantly lower mass compared to the prototype and is not inferior to it in terms of rigidity, strength and minimum values of natural vibration frequencies. The article describes the implementation of the production process for creating a workpiece using selective laser melting technology. The development of a 3D model of the design sample was carried out in the Siemens NX software. For the considered design, the method of residual stress compensation based on the optimization of heat sinks on the technological construction platform and the method of preliminary correction of the workpiece geometry in the SimufactAdditive software were applied. The results obtained in the work show the possibility of introducing additive manufacturing together with topological optimization in the design of spacecraft, including the load-bearing structures of their propulsion systems.

Secure Edge-Based Energy Management Protocol in Smart Grid Environments with Correlation Analysis

For the monitoring and processing of network data, wireless systems are widely used in many industrial applications. With the assistance of wireless sensor networks (WSNs) and the Internet of Things (IoT), smart grids are being explored in many distributed communication systems. They collect data from the surrounding environment and transmit it with the support of a multi-hop system. However, there is still a significant research gap in energy management for IoT devices and smart sensors. Many solutions have been proposed by researchers to cope with efficient routing schemes in smart grid applications. But, reducing energy holes and offering intelligent decisions for forwarding data are remain major problems. Moreover, the management of network traffic on grid nodes while balancing the communication overhead on the routing paths is an also demanding challenge. In this research work, we propose a secure edge-based energy management protocol for a smart grid environment with the support of multi-route management. It strengthens the ability to predict the data forwarding process and improves the management of IoT devices by utilizing a technique of correlation analysis. Moreover, the proposed protocol increases the system's reliability and achieves security goals by employing lightweight authentication with sink coordination. To demonstrate the superiority of our proposed protocol over the chosen existing work, extensive experiments were performed on various network parameters.

An Asynchronous Maximum Independent Set Algorithm By Myopic Luminous Robots On Grids

Abstract We consider the problem of constructing a maximum independent set with mobile myopic luminous robots on a grid network whose size is finite but unknown to the robots. In this setting, the robots enter the grid network one by one from a corner of the grid, and they eventually have to be disseminated on the grid nodes so that the occupied positions form a maximum independent set of the network. We assume that robots are asynchronous, anonymous, silent and they execute the same distributed algorithm. In this paper, we propose two algorithms: The first one assumes that the number of light colors of each robot is three and the visible range is two, but uses the additional assumption that a local edge-labeling exists for each node. To remove this assumption, the second one assumes that the number of light colors of each robot is seven, and that the visible range is three. In both algorithms, the number of movements is $O(n(L+l))$ steps, where $n$ is the number of nodes and $L$ and $l$ are the grid dimensions.

Economic Assessment of Demand Response Using Coupled National and Regional Optimisation Models

In this work, we investigate the economic viability of demand response (DR) as a balancing option for variable renewable energies, such as wind and solar. Our assessment is based on a highly resolved national energy system model for Germany coupled with a regional DR optimisation model. First, this allows us to determine the spatially resolved flexibility demand, e.g., for avoiding transmission grid congestion. Second, a high number of DR technologies from the residential, commercial and industrial sector, as well as sector coupling, can be considered to cover the regional flexibility demand. Our analysis is based on a scenario for 2035 with a 66% share of renewable energy sources in the power generation. The results show that the largest DR capacity is being installed in the west of Germany, an area with a high density of population and industry. All DR units have an aggregated capacity below 100 MW per transmission grid node. For the economic assessment, we further differentiate between two cases. In the first case with full DR cost consideration, the optimisation selects only large-scale technologies with low specific investment costs. The second case assumes that the required communication components are already installed. Here, we consider only variable costs and disregard the investment costs. As a result, several small-scale DR technologies are used, such as e-mobility. We publish the developed methodology as an open-source model, which allows reuse for other scientific purposes.

Mapping the kinematic parameters of the Galaxy from the Gaia EDR3 red giants and sub-giants

ABSTRACT We present the results of a kinematic analysis of red giants and sub-giants whose centroids are in the plane of our Galaxy. For this, the positions, parallaxes, proper motions, and radial velocities of these stars from the Gaia EDR3 catalogue were used. We applied two approaches to obtain kinematic parameters. The first approach – solving the equations of the Ogorodnikov–Milne model with respect to 12 unknowns – is generally accepted, but has a number of disadvantages. The second approach applied by us is to find the Galactocentric centroid velocity components and their partial derivatives with respect to coordinates from the solution of formal equations for the scalar stellar velocity field. To calculate the kinematic parameters by the methods mentioned above, same stellar samples were used. From these samples spherical regions with a radius of 1 kpc were selected, the centers of which were located strictly in the Galactic mid-plane at the nodes of the coordinate grid (xgal, ygal) of a rectangular Galactocentric coordinate system with step 100 pc. The investigated region of the Galaxy is located approximately in coordinate ranges 120° < θ < 240°, 0 kpc <R < 16 kpc, –1 kpc <z <1 kpc. We show the behaviour of kinematic parameters depending on the Galactocentric coordinates. The kinematic parameters as a function of Galactic coordinates were derived for the first time. Also, for the first time, the parameters ∂VR/∂θ and ∂Vθ/∂θ were derived.

Fluid–shell structure interactions with finite thickness using immersed method

This study presents a computational framework for simulating shell structures interacting with fluids using the immersed approach. The approach captures the complex movement and motion of a thin structure represented with shell elements that have a finite thickness. Utilizing the concept of the immersed approach, the fluid domain is described using a fixed set of Eulerian grids and the shell structure uses finite element shell Lagrangian descriptions, thus allowing non-intrusive coupling of independent fluid and shell finite element solvers. Different from the traditional immersed boundary method where the boundary cannot replicate the thickness of the thin boundary or shell structures, our approach projects the shell structure along the directions normal to the shell surface based on a given thickness to create a volumetric structure. Such projection allows robust, accurate and realistic interfacial loading and immersed geometry when interacting with the surrounding fluid. The dynamic solution of the mid-surface obtained from the shell solver is extended and extrapolated into the thickness direction, which is then used to calculate the forces acting on the Eulerian grid nodes to manage the effects of the overlapping solid. The volume representation also helps in calculating consistent nodal forces and moments acting on the shell surface. In particular, the moments yielded across the thickness capture the additional bending that would otherwise be missed for an infinitely thin boundary. Allowing the volumetric representation of the thin shell thickness, deformation modes such as bending and shearing can be more accurately calculated. Intricate transformations between local shell element coordinate and global coordinate were also considered to enable the coupling process. The presented fluid–shell coupling algorithm is carefully verified and validated using three numerical test cases. The accuracy and the robustness of the results also demonstrate the versatility of the developed coupling technique for thin shells and structures with finite thickness.

Experimental Validation of a Novel Methodology for Electromigration Assessment in On-Chip Power Grids

A recently proposed theoretical methodology for the assessment of the electromigration (EM) induced IR-drop degradation in on-chip power/ground grids has been validated by means of measurements performed on real silicon. A voltage tapping technique was employed for the direct measurement of voltage variations at 162 nodes of the power net, stressed with 10 mA constant source current at an elevated temperature of 350 °C. A voltage drop between cathode and anode pads exceeding a specified threshold was considered as a failure. Times-to-failure (TTF) was measured on 19 packaged test grids and used for computing the mean TTF (MTTF). The EM-induced voltage degradation in this grid was also analyzed with an assessment methodology based on a simulation of stress evolution everywhere in the grid, resulting in a voiding in some of grid branches and corresponding resistance increase. A set of voiding compact models for different grid segments was developed and used in the simulations. The stochastic nature of the EM phenomenon was captured by introducing random distributions of atomic diffusivities and critical stresses across the grid and iterating them with Monte Carlo loops. A good fit between the measured voltage evolution kinetics at different grid nodes and that predicted by simulation, and the good agreement between measured and simulated failure distributions can be considered as the ever first experimental validation of this EM assessment methodology for on-chip power/ground (p/g) grids.

An Edge-AI Based Forecasting Approach for Improving Smart Microgrid Efficiency

Smart Grid 2.0 is the energy Internet based on advanced metering infrastructure and distributed systems that require an instantaneous two-way flow of energy information. Edge computing benefits from its proximity to the servers and edge nodes of the smart grid distributed systems, which can provide efficient and low latency information transmission to the smart grid. With the massive number of Internet of Things being used, the amount of real-time power usage information generated by that represents a huge challenge for edge computing. To improve the efficiency of information transmission and processing in power systems, this article combines different deep learning algorithms with edge computing to analyze and process distributed renewable energy generation and consumer power data in smart microgrid. Experiments on two real-world datasets from China and Belgium show that the proposed framework can obtain satisfactory prediction accuracy compared to existing approaches.

The Local Nonpolynomial Splines and Solution of Integro-Differential Equations

The application of the local polynomial splines to the solution of integro-differential equations was regarded in the author’s previous papers. In a recent paper, we introduced the application of the local nonpolynomial splines to the solution of integro-differential equations. These splines allow us to approximate functions with a presribed order of approximation. In this paper, we apply the splines to the solution of the integro-differential equations with a smooth kernel. Applying the trigonometric or exponential spline approximations of the fifth order of approximation, we obtain an approximate solution of the integro-differential equation at the set of nodes. The advantages of using such splines include the ability to determine not only the values of the desired function at the grid nodes, but also the first derivative at the grid nodes. The obtained values can be connected by lines using the splines. Thus, after interpolation, we can obtain the value of the solution at any point of the considered interval. Several numerical examples are given.

Campus Microgrid Data-Driven Model Identification and Secondary Voltage Control

Microgrids deal with challenges presented by intermittent distributed generation, electrical faults and mode transition. To address these issues, to understand their static and dynamic behavior, and to develop control systems, it is necessary to reproduce their stable operation and transient response through mathematical models. This paper presents a data-driven low-order model identification methodology applied to voltage characterization in a photovoltaic system of a real campus microgrid for secondary voltage regulation. First, a literature review is presented focusing on secondary voltage modeling strategies and control. Then, experimental data is used to estimate and validate a low-order MIMO (multiple input–multiple output) model of the microgrid, considering reactive power, solar irradiance, and power demand inputs and the voltage output of the grid node. The obtained model reproduced the real system response with an accuracy of 88.4%. This model is used for dynamical analysis of the microgrid and the development of a secondary voltage control system based on model predictive control (MPC). The MPC strategy uses polytopic invariant sets as terminal sets to guarantee stability. Simulations are carried out to evaluate the controller performance using experimental data from solar irradiance and power demand as the system disturbances. Successful regulation of the secondary voltage output is obtained with a fast response despite the wide range of disturbance values.

Automated Cybersecurity Tester for IEC61850-Based Digital Substations

Power substations are the crucial nodes of an interconnected grid, serving as the points where power is transferred from the transmission/distribution grids to the loads. However, interconnected cyberphysical systems and communication-based operations at substations lead to many cybersecurity vulnerabilities. Therefore, more sophisticated cybersecurity vulnerability analyses and threat modeling are required during productization phases, and system hardening is mandatory for the commercialization of products. This paper shows the design and methods to test the cybersecurity of multicast messages for digital substations. The proposed vulnerability assessment methods are based on the semantics of IEC61850 Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV), and cybersecurity features from IEC62351-6. Different case scenarios for cyberattacks are considered to check the vulnerabilities of the device under test (DUT) based on the IEC62351-6 standard. In order to discover security vulnerabilities in a digital substation, the proposed cybersecurity tester will generate malicious packets that compromise the regular functionality. The results show that the proposed cybersecurity testing module is able to detect potential vulnerabilities in multicast messages and the authentication methods (e.g., message authentication code) of multicast communications. Both commercial and simulated devices are used for the case studies.

Third-order scale-independent WENO-Z scheme to achieve optimal order at critical points

Our past work has shown that when the critical points occur within grid intervals, the relations of accuracy of the smoothness indicators of weighted essentially non-oscillatory schemes (WENO) reported by Jiang and Shu differ from those that are obtained by assuming that the critical points occur on the grid nodes. The global smoothness indicator in the WENO-Z scheme might accordingly differ from the original one. We use this understanding to first discuss several issues regarding current improvements to third-order WENO-Z (e.g., WENO-NP3, -F3, -NN3, and -PZ3), i.e., numerical results with scale dependence, the validity of the analysis by assuming that the critical points occur on the nodes, and sensitivity in terms of the computational time step and initial conditions through the examination of the order of convergence. Numerical simulations and analyses were used to highlight defects in these improvements that occur either due to the scale dependence of the results, or the failure to recover the optimal order when the critical points occur on the half-nodes. Following this, a generic analysis that assumes that the first-order critical points occur within the grid intervals is provided. The theoretical results thus derived are used to propose two scale-independent third-order WENO-Z schemes that can be used to attain the optimal order at the critical points. The first scheme is obtained by extending a downstream smoothness indicator to derive a new global smoothness indicator and incorporating it into the mapping function. The second scheme is achieved by extending another smoothness indicator and using a different global indicator. The following validations are chosen and tested: the typical 1D problem of scalar advections, and 1D and 2D problems based on Euler's equations. The results verify the capability of the proposed schemes to recover the optimal order at the critical points. Moreover, the first of the above two proposed schemes outperforms the improved third-order WENO-Z scheme in terms of numerical resolution and robustness, which is usually favored by applications.

Mechanical behavior analyses of 4D printed metamaterials structures with excellent energy absorption ability

Mechanical metamaterials with immense specific energy absorption and high specific strength are extensively being applied in engineering fields, including bone tissue scaffolds, aerospace and automotive engineering. Many structural design strategies have been developed to improve their mechanical properties. The lattice metamaterials with a tremendous specific energy absorption capacity exhibit continual platform stress after initial yield and before densification. Here, combined with bionic design, we designed and fabricated a series of mechanical metamaterial with tension-dominated mechanical behavior which can assimilate enormous amounts of energy while maintaining a low density. The design strategy relied on the network construction in the periodic grid topology, which took the microstructure with several beams as the building block connecting the grid nodes. The mechanical properties can be adjusted by changing topology parameters. Additionally, the metamaterials fabricated by 4D printing technology show intelligent properties, which can jump from one mode to another under external stimulation. It was worth mentioning that the shape memory effect (SME) also endowed the material with certain self-healing properties. Excellent compressive resistance, energy absorption, shock absorption and shape memory effect suggest the application prospect in engineering fields.

Fast iterative method for seismic wave travel time calculation under undulating surface conditions

Seismic wave travel time is an important seismic attribute information and is widely used in various seismic forward and inversion methods, including seismic migration imaging, seismic tomography, seismic wave forward modeling and other core seismic data processing methods. The accuracy and efficiency of the travel time algorithm are important for the above methods. In the practical application of seismic exploration, it is often carried out under the condition of undulating surface, which has a significant impact on the travel time calculation. Therefore, it is of great significance to study an efficient and high-precision travel time calculation method that can adapt to undulating surface condition. In this paper, Fast iterative method (FIM) is modified to a topography travel time calculation method. The method employs an iterative method to solve the equation of function to obtain seismic wave travel time by maintaining a narrow band called the active list, and the algorithm can update all grid nodes in the active list at a time. We will verify the travel time computing power of the FIM method through several different velocity models.

Development of measures to reduce grid energy losses in the Namangan Region of Uzbekistan

The paper is aimed at developing technical and organizational measures to reduce the losses of electrical energy during its transmission via main and distribution electrical grids, in power transformers and electric power trans-mission lines. The focus of the study was on electrical grid modes in the Namangan Region of Uzbekistan (voltages of 220/110/35/10/6 kV), which were analyzed via technological calculation-based research methods using an equivalent circuit representing the linear circuit currently employed in the regional electric energy system. In addition, electrical grids were simulated using the software package “Program for calculating electrical grid modes” followed by the processing of calculation results by means of the Microsoft Excel package. The paper calculates electrical modes for the equivalent circuit of the regional electric energy system, as well as offering technical measures (installation of reactive power compensation devices; adjustment of transformation ratios in power transformers) aimed at adjusting voltage to improve electric power quality in terms of voltage deviations and lower power losses. Voltage deviations in most grid nodes were found to be inconsistent with GOST 32144-2013. Thus, in 35 kV, 10 kV, and 6 kV nodes, the largest underdeviation amounted to 12.45 kV, 3.26 kV, and 2.09 kV, respectively. For the placement of reactive power compensating devices having a total power of 67.82 MV∙Ar, 35 kV nodes were used; in addition, the values of transformer ratios at transformer substations (35–110 kV) were determined. Calculations indicate that the conducted activities can normalize voltage in the 35 kV, 10 kV, and 6 kV nodes while reducing power losses in the electrical grid by 9.35 MW. It is estimated that the proposed measures will be paid back in approximately three years. By means of compensating reactive power and adjusting transformer ratios, these measures can reduce electrical energy losses during transmission in the considered objects and maintain a given voltage level.

Local mesh deformation using a dual-restricted radial basis functions method

In order to study the motion of a deformable configuration in the air flow, mesh deformation technology is essentially needed. The radial basis function (RBF) interpolation algorithm is a popular mesh deformation algorithm. For local mesh deformation, such as aeroelastic response simulation of aircraft components and deflection of flight control surface, we do not need to move all grid nodes. On the contrary, only part of the mesh near the deformation boundary needs to be moved. If we can limit the deformation range caused by the RBF method to a small region, the computational cost could be saved. In addition to the consideration of efficiency, another reason is that in the position optimization of aircraft components, we need to keep most of the meshes unchanged to reduce the error caused by mesh inconsistency. In the previous research [24], a restricted RBF interpolation algorithm was constructed and coupled with a multi-level interpolation technique to reduce the volume mesh nodes for global mesh deformation problem. The restricted RBF method is improved in the current research and a so-called dual-restricted RBF algorithm is proposed. This new method constructs a restricting function using the distance both to the moving and static boundaries so that the stationary wall could be preserved exactly. Theoretical analysis and numerical examples also have confirmed that the new algorithm is beneficial to improve the efficiency of mesh deformation process compared with the restricted RBF algorithm because mesh nodes near the stationary boundary no longer need to be moved.

Three-Dimensional Image of Crustal Density Model: A Case Study in South Kamchatka

Abstract —The methodology for building a 3D density model of the Earth’s crust and upper mantle for a crustal block in the South Kamchatka Peninsula is presented. The model is derived from the interpretation of the Bouguer anomaly values and data obtained by deep seismic soundings and electrical prospecting methods. 3D image creation can be viewed as a several phase procedure. At the first step, the area of interest is investigated through a network of intersecting profiles utilized for subsequent modeling depth density sections using the parameter scanning procedure. The a priori data include materials of geophysical surveys and geological, and petrophysical studies as well as results of depth estimation at singular points by the Euler deconvolution method. The next step involves formation of a 3D density matrix from the cross-section models. Coordinates in the cross-section planes are defined in the square grid nodes and converted to plane rectangular coordinates (the SK-42 reference system). A file of the cross-sectional database of density values is thus produced. For area shaving a sparse network of cross-sections, an additional database is derived from grid files of densities mapped horizon-wise. This ultimately results in the creation of the unified databases. A 3D network of cubic unit cells for three-dimensional (voxel) representation of density of the geologic medium is calculated. The model of density of unit cube with edge measuring 4 km was constructed for entire investigated block of the Earth’s crust. The model was detailed by decreasing successively the unit cube edges to 2.0, 1.0, and 0.5 km. The 3D modeling results are presented as block diagrams and density isosurface maps in horizontal slices at different depths. The block diagrams show isosurfaces with densities typical of deep subsurface boundaries and structures. The isosurfaces for densities of 2.75 and 2.90 g/cm3 reflect the morphology of the roof of the crystalline basement, and the lower–upper crust boundary, respectively, while the isosurfaces of 3.20 and 3.33 g/cm3 represent feasible shape of the crust–upper mantle contact. The lower-density zone ubiquitously observed in the investigated crustal block is caused by rock destruction along the deep fault. It is identified in the model with 1 km cubic unit cell side and encompasses the feeding systems of volcanoes, namely: Sopka Asacha (Asacha Volcano), Mutnovskaya Sopka (Mutnovsky Volcano), Gorelaya Sopka (Gorely Volcano), and Vilyuchinskaya Sopka (Vilyuchansky Volcano).The model with a 0.50 km cubic unit cell side shows a 2.85 g/cm3 isosurface, which delineates a column-shaped high-density region. A higher density revealed in the block is assumed to be associated with basite intrusions. 3D density models based on cross-section modeling provide additional information for geodynamic reconstructions, allowing a rough estimation of the geometry of concealed geologic features and their volumes, and can be utilized in 3D modeling to build initial models.

A new hybrid CRWENO-MWENOZ-adaptive moving mesh method for cavitating two-phase compressible fluid flow simulation

In this paper, a high-order hybrid method for solving compressible two-phase fluid flow, including cavitation, is presented. In this regard, assuming pressure and temperature equilibrium, mass and heat transfer between the different phases are modeled. In this work, the CRMWENOZ method, which is a new combination of compact and weighted essentially non-oscillatory (WENO) methods and is more accurate than conventional methods, is presented. The new high-order hybrid method aims to predict the density and the pressure discontinuities in two-phase flow by combining the CRMWENOZ high-order method and an adaptive moving mesh technique. For this purpose, the adaptive moving mesh partial differential equation (MMPDE) method would also improve the accuracy of results by concentrating on the grid nodes in high-gradient regions for transient flows. Applying the CRMWENOZ method alongside MMPDE and using the fifth-order Radau method for time discretization lead to a substantial improvement in the accuracy of simulation, particularly near the liquid–gas interfaces. The accuracy of the proposed hybrid method was compared to other studies’ predictions of one-dimensional (1D) expansion and shock tube problems containing two-phase flow with and without cavitation. The results showed that the hybrid method presented was more accurate than the usual two-phase flow methods while using a reasonable amount of computer resources.

The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)

Abstract. Classical numerical models for the global atmosphere, as used for numerical weather forecasting or climate research, have been developed for conventional central processing unit (CPU) architectures. This hinders the employment of such models on current top-performing supercomputers, which achieve their computing power with hybrid architectures, mostly using graphics processing units (GPUs). Thus also scientific applications of such models are restricted to the lesser computer power of CPUs. Here we present the development of a GPU-enabled version of the ICON atmosphere model (ICON-A), motivated by a research project on the quasi-biennial oscillation (QBO), a global-scale wind oscillation in the equatorial stratosphere that depends on a broad spectrum of atmospheric waves, which originates from tropical deep convection. Resolving the relevant scales, from a few kilometers to the size of the globe, is a formidable computational problem, which can only be realized now on top-performing supercomputers. This motivated porting ICON-A, in the specific configuration needed for the research project, in a first step to the GPU architecture of the Piz Daint computer at the Swiss National Supercomputing Centre and in a second step to the JUWELS Booster computer at the Forschungszentrum Jülich. On Piz Daint, the ported code achieves a single-node GPU vs. CPU speedup factor of 6.4 and allows for global experiments at a horizontal resolution of 5 km on 1024 computing nodes with 1 GPU per node with a turnover of 48 simulated days per day. On JUWELS Booster, the more modern hardware in combination with an upgraded code base allows for simulations at the same resolution on 128 computing nodes with 4 GPUs per node and a turnover of 133 simulated days per day. Additionally, the code still remains functional on CPUs, as is demonstrated by additional experiments on the Levante compute system at the German Climate Computing Center. While the application shows good weak scaling over the tested 16-fold increase in grid size and node count, making also higher resolved global simulations possible, the strong scaling on GPUs is relatively poor, which limits the options to increase turnover with more nodes. Initial experiments demonstrate that the ICON-A model can simulate downward-propagating QBO jets, which are driven by wave–mean flow interaction.

Integration within Fluid Dynamic Solvers of an Advanced Geometric Parameterization Based on Mesh Morphing

Numerical optimization procedures are one of the most powerful approaches with which to support design processes. Their implementation, nevertheless, involves several conceptual and practical complexities. One of the key points relates to the geometric parameterization technique to be adopted and its coupling with the numerical solver. This paper describes the setup of a procedure in which the shape parameterization, based on mesh morphing, is integrated into the analysis tool, accessing the grid nodes directly within the solver environment. Such a coupling offers several advantages in terms of robustness and computational time. Furthermore, the ability to morph the mesh “on the fly” during the computation, without heavy Input/Output operations, extends the solver’s capability to evaluate multidisciplinary phenomena. The procedure was preliminary tested on a simple typical shape optimization problem and then applied to a complex setup of an industrial case: the identification of the shape of a Volvo side-view mirror that minimizes the accumulation of water on the lens of a camera mounted beneath.