Selection Of Configuration Research Articles

Desensitization design of freeform off-axis TMA optical systems with configuration selection

The off-axis three-mirror anastigmatic (TMA) optical system has the advantages of eliminating all primary aberrations, having no aperture obscuration, no chromatic aberration, and good environmental adaptability, making it essential in high-performance optical instruments. Freeform surfaces, with their rich degrees of freedom (DOFs) in mathematical representation, positively affect the image quality and sensitivity of optical systems. When applied correctly to off-axis TMA optical systems, they can achieve fast F-numbers, large fields of view (FOVs), and long focal lengths. There are dozens of configurations for off-axis TMA optical systems, and freeform surfaces can be combined in numerous ways within these systems. This paper first analyzes the sensitivity of off-axis TMA optical systems with different configurations, selects the configuration with the lowest sensitivity, and combines it with a low sensitivity freeform surface combination to achieve high-performance freeform off-axis TMA optical systems with low sensitivity.

Optimizing reconfigurable manufacturing system configuration selection with multi-objective grey wolf optimization

Optimizing reconfigurable manufacturing system configuration selection with multi-objective grey wolf optimization

Selective collaboration in distributed FxLMS active noise control systems

This paper addresses the selection of the collaboration configuration on distributed active noise control (ANC) systems. ANC systems aim to cancel out acoustic noise within a listening area. In distributed systems, the control task is delegated among multiple acoustic control nodes that generate the control signals by filtering a noise reference signal. The coefficients of each node filter are iteratively calculated using the filtered-X LMS algorithm. The stability is achieved when the adaptive filters computed in each node converge to finite values. However, acoustic coupling among nodes could lead to instability (i.e., divergence). Collaboration among selected nodes may avoid this phenomenon, although not just any collaboration configuration guarantees network stability. On the other hand, a collaborative distributed system presents two drawbacks: the stability assessment is computationally expensive, and communication requirements increase with the number of collaborations among nodes. In this paper, we propose and discuss several methods to establish a collaboration configuration that ensures system stability. The optimal configuration, which is characterized by the minimal number of necessary collaborations between nodes, can be identified through exhaustive search. However, this approach incurs a high computational cost, particularly in networks with many nodes. To address this challenge, we introduce several heuristic methods aimed at efficiently obtaining stable configurations.

A conflict risk graph approach to modeling spatio-temporal dynamics of intersection safety

Intersections are among the most hazardous roadway spaces due to the complex and conflicting road users’ movements. Spatio-temporal modeling of conflict risks among road users can help to identify strategies to mitigate the exacerbation of safety risks and restore hazardous conditions to normal traffic situations. This paper proposes the 'Conflict Risk Graph' as a novel concept to infer real-time conflict risks at intersections at a fine-grained level by mapping conflict-prone locations to nodes within a network characterized by specific topological structures. A significant contribution of this work is the development of a Transformer-based Graph Convolutional Network (Trans-GCN), a model that synergistically combines the Transformer's proficiency in capturing global dependence with the GCN's ability to learn local correlations. The Trans-GCN adeptly models the complex evolution patterns of conflict risks at intersections. The evaluation in this paper against five common state-of-the-art deep learning approaches demonstrates the superior performance of the Trans-GCN in conflict risk inference and adaptability to node changes. Furthermore, extensive experiments with different node configurations reveal a correlation between node setup and model performance, showing that higher spatio-temporal resolution decreases inference accuracy. This insight informs the selection of an optimal node configuration that balances the detailed capture of spatio-temporal dynamics with modeling accuracy, enabling ideal conflict risk inferences at intersections. Ultimately, this work offers significant insights for the enhancement of proactive traffic safety management and the advancement of intelligent traffic systems.

Projective Spin Adaptation for the Exact Diagonalization of Isotropic Spin Clusters

Spin Hamiltonians, like the Heisenberg model, are used to describe the magnetic properties of exchange-coupled molecules and solids. For finite clusters, physical quantities, such as heat capacities, magnetic susceptibilities or neutron-scattering spectra, can be calculated based on energies and eigenstates obtained by exact diagonalization (ED). Utilizing spin-rotational symmetry SU(2) to factor the Hamiltonian with respect to total spin S facilitates ED, but the conventional approach to spin-adapting the basis is more intricate than selecting states with a given magnetic quantum number M (the spin z-component), as it relies on irreducible tensor-operator techniques and spin-coupling coefficients. Here, we present a simpler technique based on applying a spin projector to uncoupled basis states. As an alternative to Löwdin’s projection operator, we consider a group-theoretical formulation of the projector, which can be evaluated either exactly or approximately using an integration grid. An important aspect is the choice of uncoupled basis states. We present an extension of Löwdin’s theorem for s=12 to arbitrary local spin quantum numbers s, which allows for the direct selection of configurations that span a complete, linearly independent basis in an S sector upon the spin projection. We illustrate the procedure with a few examples.

The role of building mass configuration and material selection for mitigating the intensity of the urban heat island

The knowledge of urban heat island (UHI) mitigation for the materials and geometry of urban areas requires enrichment. This study compares to the thermal conditions on two different building mass configurations (Superblock and horizontal residential areas), that involve geometry aspect (density, orientation) and materials aspect (softscape, pavement, roof, wall). A surface urban heat island (SUHI) survey was conducted using Landsat thermal imagery, followed by ground surveys in selected areas. Data collected in both areas included air temperature, relative humidity, air velocity, and globe temperature area. The results show that the superblock configuration had a low SUHI intensity due to the proportional orientation of East-West-North-South (0.56–0.44) and large shading (average of 0.31 m2). In contrast, in the dense residential areas, the intensity of SUHI was high because the proportion of East-West walls was wider than North-South (0.8–0.2), and the shading was low (average of 0.15–0.16 m2). Façade and ground heating occurred owing to the use of heavy-weight materials, which was indicated in the thermal imagery, with a solar heating index in a vertical cluster mass configuration of 21.7 and a horizontal grid of 55.9. Convective cooling occurred in a vertical geometry because the buildings generated turbulence that removed warm air, whereas it did not occur in a horizontal geometry. The convective cooling index for the vertical cluster mass configuration was 0.62, whereas that for the horizontal grid configuration was 0.09. This indicates that regional planning must incorporate geometric and material considerations to control the urban thermal environments.

Hyperparameter optimization of regional hydrological LSTMs by random search: A case study from Basque Country, Spain

This paper introduces a novel approach for hyperparameter optimization of long short-term memory networks (LSTMs) to achieve highly accurate hourly streamflow and water level predictions in the realm of regional rainfall-runoff modeling. Leveraging simultaneous systematic hyperparameter optimization of 10 distinct hyperparameters by Random Search, the study achieves high accuracy in terms of predictions across 40 humid flashy catchments in Basque Country, north of Spain. By carefully designing the search space and incorporating domain expertise, the approach quickly converges to optimal and highly accurate network configurations with both efficiency and efficacy. LSTMs ingested precipitation, temperature, and potential evapotranspiration as inputs to predict 2 targets of streamflow and water level, in an hourly timestep. On the test set, the optimized LSTM networks accurately predicted streamflow and water level with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) efficiencies as high as 0.97, in one of the catchments. Across all 40 studied catchments, the overall average NSE and KGE values for streamflow were 0.89 and 0.87, respectively; water level exhibited average NSE and KGE scores of 0.91 and 0.92.Moreover, statistical analysis reveals significant differences in the performance of the 2 distinct optimized network architectures in different hydrological catchments, underscoring the importance of deliberate network configuration selection post-random search. This selection process is vital for achieving higher performance in as many catchments as possible. The findings highlight opportunities for enhancing the “learning maturity” of regional hydrological deep learning LSTM networks. This research provides valuable insights for researchers and practitioners involved in optimizing regional hydrological deep learning models for a variety of applications and on new datasets.

Asymmetric Cu−N1O3 Sites Coupling Atop‐type and Bridge‐type Adsorbed *C1 for Electrocatalytic CO2‐to‐C2 Conversion

Abstract2D functional porous frameworks offer a platform for studying the structure–activity relationships during electrocatalytic CO2 reduction reaction (CO2RR). Yet challenges still exist to breakthrough key limitations on site configuration (typical M−O4 or M−N4 units) and product selectivity (common CO2‐to‐CO conversion). Herein, a novel 2D metal–organic framework (MOF) with planar asymmetric N/O mixed coordinated Cu−N1O3 unit is constructed, labeled as BIT‐119. When applied to CO2RR, BIT‐119 could reach a CO2‐to‐C2 conversion with C2 partial current density ranging from 36.9 to 165.0 mA cm−2 in flow cell. Compared to the typical symmetric Cu−O4 units, asymmetric Cu−N1O3 units lead to the re‐distribution of local electron structure, regulating the adsorption strength of several key adsorbates and the following catalytic selectivity. From experimental and theoretical analyses, Cu−N1O3 sites could simultaneously couple the atop‐type (on Cu site) and bridge‐type (on Cu−N site) adsorption of *C1 species to reach the CO2‐to‐C2 conversion. This work broadens the feasible C−C coupling mechanism on 2D functional porous frameworks.

Numerical Evaluation of the performance of different composite bridge decks.

Abstract A comparative analysis was conducted to facilitate the selection of composite bridge deck configurations. Composite bridge decks, with their lightweight design, corrosion resistance, prefabrication, reduced construction time, and wide design flexibility, reduce substructure costs and offer durability. Static and buckling analyses were conducted using finite element software to compare their weight, stiffness, composite inverse reverse factor, and buckling resistance. The analyses considered the same boundary conditions, loads, composite layup configuration, and material mechanical properties. Various geometries were selected from different literature to evaluate their performance and identify an appropriate design. This paper presents a numerical investigation into the structural performance of five different composite bridge decks under the same conditions. G. Rectangle emerged as the easiest manufacturing deck, consisting of pultruded rectangle tubes, and the worst deck for deflection and buckling. The G. Triangle has the lowest deflection and the highest strain energy density. The G. Arch distinguished as the lightest bridge deck, also has good performance against buckling and a low strain energy density. Finally, the G. 2Trapezoidal and G. Trapezoidal have better total performance than all other decks as they have the highest inertia.

Optimal configuration selection in reconfigurable manufacturing system considering variable production rate

Various manufacturing companies produce different components, parts, or entire products based on market demands. These needs are met by a variety of manufacturing systems. However, in today's dynamic environment where production capacities and company capabilities are subject to change, reconfigurable manufacturing systems (RMS) have emerged as crucial resources. At the heart of RMS lies the reconfigurable machine tool (RMT), which is designed with modular components to adapt to varying requirements. Evaluating the performance of RMS requires an index. This paper employs weighted sum theory to map various characteristics of RMS and develop a cumulative reconfigurability index. To illustrate the applicability of this methodology, a case study is presented, examining both machine and system levels. There are four configurations having eight RMTs arranged in different manner. The cumulative reconfigurability index is calculated for each configuration and the optimal configuration is selected. From this research, it has been observed that the reconfigurability index of system (d) is the highest, with system (a) having a value close to that of system (d).

Azologs of the Fatty Acid Mimetic Drug Cinalukast Enable Light-Induced PPARα Activation.

Photo-switchable nuclear receptor modulators ("photohormones") enable spatial and temporal control over transcription factor activity and are valuable precision tools for biological studies. We have developed a new photohormone chemotype by incorporating a light-switchable motif in the scaffold of a cinalukast-derived PPARα ligand and tuned light-controlled activity by systematic structural variation. An optimized photohormone exhibited PPARα agonism in its light-induced (Z)-configuration and strong selectivity over related lipid-activated transcription factors representing a valuable addition to the collection of light-controlled tools to study nuclear receptor activity.

Investigating novel perovskites of lead-free flexible solar cell CH3NH3BiI3 and their photovoltaic performance with efficiency over 26%

Perovskite solar cells are increasing attention due to their unique characteristics in the field of photovoltaic technology. Lead-based perovskite solar cells are particularly notable for their high efficiency. However, their commercial production is limited because of the use of lead-based absorbers. As a result, research has shifted towards exploring lead-free alternatives in the realm of perovskite materials. This study utilizes SCAPS-1D simulation software to optimize the performance of a lead-free flexible solar cell. Lead (Pb), a group 14 element, is proposed to be replaced by bismuth (Bi), a group 15 element. We investigate how the selection of configurations for the Electron Transport Layer (ETL), Hole Transport Layer (HTL), and absorber layer impacts solar cell performance. This study represents a comprehensive examination of this material. The device optimization involves using a fluorine-doped tin oxide (FTO) substrate, cadmium sulfide (CdS), tungsten disulfide (WS2), titanium dioxide (TiO2), and fullerene (C60) as ETL components, methyl ammonium bismuth iodide (CH3NH3BiI3) as the absorber, molybdenum disulfide (MoS2) as the HTL, and platinum (Pt) as the electrode. In addition to optimizing ETL and HTL configurations, this study explores the effects of various factors such as absorber, ETL, and HTL thickness, shunt and series resistance, temperature variations, Mott-Schottky behavior, capacitance, recombination, generation rates, J-V characteristics, and quantum energy. The results show that the solar cell configuration using FTO/CdS/CH3NH3BiI3/MoS2/Pt achieves an efficiency of 26.60 %, a current density (JSC) of 32.02 mA/cm2, an open circuit voltage (VOC) of 0.974 V, and a fill factor (FF) of 85.24 %. This represents a significant improvement compared to previous research. This detailed simulation analysis enables researchers to develop cost-effective and highly efficient perovskite solar cells (PSCs), driving advancements in solar technology.

Versatile, modular, and customizable magnetic solid-droplet systems

Magnetic miniature robotic systems have attracted broad research interest because of their precise maneuverability in confined spaces and adaptability to diverse environments, holding significant promise for applications in both industrial infrastructures and biomedical fields. However, the predominant construction methodology involves the preprogramming of magnetic components into the system's structure. While this approach allows for intricate shape transformations, it exhibits limited flexibility in terms of reconfiguration and presents challenges when adapting to diverse materials, combining, and decoupling multiple functionalities. Here, we propose a construction strategy that facilitates the on-demand assembly of magnetic components, integrating ferrofluid droplets with the system's structural body. This approach enables the creation of complex solid-droplet robotic systems across a spectrum of length scales, ranging from 0.8 mm to 1.5 cm. It offers a diverse selection of materials and structural configurations, akin to assembling components like building blocks, thus allowing for the seamless integration of various functionalities. Moreover, it incorporates decoupling mechanisms to enable selective control over multiple functions, leveraging the fluidity, fission/fusion, and magneto-responsiveness properties inherent in the ferrofluid. Various solid-droplet systems have validated the feasibility of this strategy. This study advances the complexity and functionality achievable in small-scale magnetic robots, augmenting their potential for future biomedical and other applications.

Automatic recognition of excavator working cycles using supervised learning and motion data obtained from inertial measurement units (IMUs)

This paper proposes an automatic method for excavator working cycle recognition using supervised classification methods and motion information obtained from four inertial measurement units (IMUs) attached to moving parts of an excavator. Monitoring and analyzing tasks that have been performed by heavy-duty mobile machines (HDMMs) are significantly required to assist management teams in productivity and progress monitoring, efficient resource allocation, and scheduling. Nevertheless, traditional methods depend on human observations, which are costly, time-consuming, and error-prone. There is a lack of a method to automatically detect excavator major activities. In this paper, a data-driven method is presented to identify excavator activities, including loading, trenching, grading, and idling, using motion information, such as angular velocities and joint angles, obtained from moving parts, including swing body, boom, arm, and bucket. Firstly, a dataset lasting 3 h is collected using a medium-rated excavator. One experienced and one inexperienced operator performed tasks under different working conditions, such as different types of material, swing angle, digging depth, and weather conditions. Four classification methods, including support vector machine (SVM), k-nearest neighbor (KNN), decision tree (DT), and naive Bayes, are off-line trained. The results show that the proposed method can effectively identify excavator working cycles with a high accuracy of 99%. Finally, the impacts of parameters, such as time window, overlapping configuration, and feature selection methods, on the classification accuracy are comprehensively analyzed.

Asymmetric Cu-N1O3 Sites Coupling Atop-type and Bridge-type Adsorbed *C1 for Electrocatalytic CO2-to-C2 Conversion.

2D functional porous frameworks offer a platform for studying the structure-activity relationships during electrocatalytic CO2 reduction reaction (CO2RR). Yet challenges still exist to breakthrough key limitations on site configuration (typical M-O4 or M-N4 units) and product selectivity (common CO2-to-CO conversion). Herein, a novel 2D metal-organic framework (MOF) with planar asymmetric N/O mixed coordinated Cu-N1O3 unit is constructed, labeled as BIT-119. When applied to CO2RR, BIT-119 could reach a CO2-to-C2 conversion with C2 partial current density ranging from 36.9 to 165.0 mA cm-2 in flow cell. Compared to the typical symmetric Cu-O4 units, asymmetric Cu-N1O3 units lead to the re-distribution of local electron structure, regulating the adsorption strength of several key adsorbates and the following catalytic selectivity. From experimental and theoretical analyses, Cu-N1O3 sites could simultaneously couple the atop-type (on Cu site) and bridge-type (on Cu-N site) adsorption of *C1 species to reach the CO2-to-C2 conversion. This work broadens the feasible C-C coupling mechanism on 2D functional porous frameworks.

Integrating energy simulations and analytical hierarchy process procedure in multi-criteria evaluation of heating systems for industrial buildings

Industrial buildings in Italy are generally aged and widely outdated from an architectural, technological, and environmental perspective. Despite the current limitations affecting both envelope and system installations, enhancement strategies are not frequently debated in the literature or addressed recurring to not adequately comprehensive approaches. This research examines space heating options for integrated retrofit interventions of manufacturing facilities using a novel methodology that combines multi-criteria decision analysis based on the Analytic Hierarchy Process (AHP) with building energy simulations. Interviews with representatives from medium-sized companies in Tuscany provide insights into the exigencies of industrial buildings, while on-site surveys identify common features of industrial buildings in the region leading to the identification of a representative case study building. This facility is examined producing several energy models to account for the different heating system alternatives to be evaluated according to criteria including economic, environmental, comfort, space, and reliability. Both qualitative judgments and quantitative outputs from energy simulations are considered to rank the technological alternatives encompassed in the analysis. In addition, sensitivity analyses are carried out to highlight the impact of boundary conditions on optimal configuration selection. Economic considerations weigh heavily for industrial owners, often outweighing environmental concerns due to higher initial investment requirements for low-impact solutions. Consequently, gas boiler generators and hot-water fan heaters emerge as preferred options for their flexibility, low initial cost, and ease of installation.

Proximal foundation anchor variations and their correlation with unplanned return to the operating room (UPROR) in children with EOS treated with magnetically controlled growing rods (MCGR).

The evolution of MCGR technique has led to modifications in the configuration of the proximal construct to decrease the incidence of implant-related complications (IRC) and revision surgeries. However, there is no data characterizing the performance of the most used configurations reducing the risk of complications. 487 patients were identified from an international multicenter EOS database. EOS patients, primary dual MCGR, complete radiographs, and minimum of 2-year follow-up. 76 patients had incomplete X-rays, 5 had apical fusions, and 18 had inconclusive complications, leaving 388 patients for review. A digital spine template was created to document UIV; number of levels; number, type, and location of anchors; as well as implant configuration. First available postoperative and latest follow-up radiographs were reviewed by two senior surgeons and two spine fellows. UPROR due to IRC was defined as any change in proximal anchors between the postoperative and final follow-up radiographs. The most common proximal construct configuration: UIV at T2 (50.0%) with 17.5% UPROR, followed by T3 (34.0%) with 12.1% UPROR; number of levels was three (57.1%) with 16.8% UPROR and two (26.0%) with 17.0% UPROR; number of proximal anchors was six (49.9%) with 14.1% UPROR and four (27.0%) with 18.3% UPROR. The most common anchors were all screws (42.0%) with 9.9% UPROR, and all hooks (26.4%) with 31.4% UPROR (P < 0.001). The construct with the lowest rate of UPROR was a UIV at T2, with six anchors (all screws) across three levels (42 cases), with 0% UPROR. Other construct combinations that yielded 0% UPROR rates were UIV of T3, six anchors (all screws) across three levels (25 cases), and a UIV of T3 with six anchors (screws and hooks) across three3 levels (9 cases). Proximal anchor configuration impacts the incidence of UPROR due to IRC in MCGR. UIV at T2 and T3 compared to T4, and the use of all screws or combination of screws and hooks compared to all hooks were associated with a lower UPROR rate. The most common construct configuration was T2 UIV, three levels, six anchors, and all screws. The use of a combination of six anchors (screws or screws and hooks) across three levels with a UIV at T2 or T3 was associated with a lower UPROR rate.Additional research is needed to further evaluate the variables contributing to configuration selection and their association with IRC.

Energy Efficient Downsizing of Ribbed Confinements for Heat Exchange Applications

Abstract Downsizing double-pipe heat exchangers is possible by deploying ribs on the two sides of the heat exchangers. The shape of these ribs, along with two key geometric variables &amp;#x96; pitch and height, are crucial in the selection of energy-efficient rib configurations. This is because, the enhancement in heat transfer performance comes at the cost of increased pressure drop. Thus, the goal of this three-dimensional numerical investigation is to identify favourable rib shapes and explore the effect of truncation on triangular ribs, something which is missing from existing literature. Truncation is expected to greatly affect the performance of triangular ribs, either adversely or favorably. To explore this conclusively, an unbiased and exhaustive analysis is carried out by comparing the performance of confinements with modified and regular triangular ribs, keeping plain confinements as the baseline. Furthermore, the effects of two principal design variables &amp;#x96; rib height and rib pitch are explored for each shape. Separate results are presented for the inner and outer confinements of the double-pipe heat exchangers (pipes and annuli) to allow for the extrapolation of results for a wide range of applications employing internal flows in pipes and annuli. A phenomenological model is developed to classify the thermo-hydraulic performance of each confinement and identify optimal geometrical configuration and identify best performing design(s). Once optimal rib pitch-height combinations are identified, performance at this optimal combination is evaluated at different Reynolds numbers, spanning from 10,000 to 30,000.

Evaluation of Noise-Reduction Techniques for Gas-Turbine Test Stands: A Preliminary Analysis

Emphasizing the importance of acoustic attenuation in maintaining compliance with stringent noise regulations and enhancing workplace safety, this analysis covers theoretical and practical aspects of prediction methods used for the development of sound attenuators for gas-turbine testing stands. This paper presents a preliminary analysis and evaluation of the improvement of the Embleton method for projecting a noise attenuator for industrial applications, especially for gas-turbine test stands. While primarily focusing on the static acoustic behavior of the attenuator, certain considerations were also made regarding flow conditions, Mach number-dependent attenuation, pressure drop, and self-generated noise aspects to provide a comprehensive perspective on applying a suitable evaluation method. The study investigates different calculation methods for the assessment of noise reduction for linear and staggered baffles applied on a scaled reduced model of an attenuator. Thus, the critical parameters and development requirements necessary for effective noise reduction in high-performance gas-turbine testing environments will be evaluated in a downscaled model. Key factors examined include the selection of design parameters and configurations from various topological options (single, double, and triple parallel baffles vs. double and triple staggered baffles). Advanced computational methods, like analytic and finite-element analysis (FEM), are used to predict acoustic performance and evaluate the prediction method. Experimental validation is performed to corroborate the simulation results, ensuring the reliability and efficiency of the attenuator. The results indicate that an improved prediction method led to a better design for a sound-attenuator module, which can significantly reduce noise levels without compromising the operational performance of the gas turbine inside a test cell.

Assessment of the Effectiveness of Energy Transfer for Shore-to-Ship Fast Charging Systems

Charging systems from shore to ship are typically designed based on a range of operational and design parameters, encompassing onboard power and propulsion needs, available charging durations, and the capacity of local power networks. In areas with weak grid infrastructure, onshore energy storage is often employed to facilitate high-power charging for vessels requiring short charging intervals. Nevertheless, incorporating on-shore energy storage adds complexity to the system, and the selection of system configuration can profoundly affect the efficiency of energy transfer from the grid to the vessel. This study presents a comparative analysis of energy efficiency among AC, DC, and Inductive shore-to-ship charging solutions for short-distance ferries utilizing both AC and DC-based propulsion systems. Findings illustrate that an increased reliance on onshore battery power correlates with decreased overall energy efficiency during the charging process. Thus, optimizing energy efficiency necessitates careful consideration when distributing the load between the grid and onshore battery. Results indicate that DC charging offers advantages over other solutions for AC-based propulsion systems in terms of energy efficiency. However, for DC-based propulsion systems, the most efficient solution may be either DC or AC charging, contingent upon the distribution of load between the grid and onshore battery. Furthermore, it is inferred that despite adding additional conversion stages and complexity to the system, the energy efficiency of inductive charging is comparable to wired schemes. Considering the added benefits of contactless charging, such as reliability, safety, and robustness, these findings advocate for the adoption of inductive charging as a promising solution.