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How to use a simple and classical topology to provide a high-efficiency excitation voltage for dielectric barrier discharge (DBD) loads is one of the primary problems to be solved for DBD application fields.

To address the issue, a set of modes that can generate a high-efficiency pulse excitation voltage in a full-bridge inverter are adopted. With the set of modes, the unique equivalent circuit of DBD loads and the parasitic parameter of the step-up transformer can be fully used. Based on the set of modes, a control strategy for the full-bridge inverter is designed. To test the performance of the power supply, a simulation model is established and an experimental prototype is made with a DBD excimer lamp.

The simulation and experimental results show that not only a high-efficiency excitation voltage can be generated for the DBD load, but also the soft switching of all power switch is realized. Besides this, with the set of modes and the proposed control strategy, the inverter can operate in a high frequency. Compared with other types of power supplies, the power supply used in the paper can fully take advantage of the potential of the excimer lamp at the same input power.

This work considers that how to use a simple and classical topology to provide a high-efficiency excitation voltage for DBD loads is one of the primary problems to be solved for DBD application fields.

The purpose of this study is to address the issue that the traditional V-shaped ball valve profile shape is limiting the flow control characteristics in a series structure and to optimize the design profile by proposing an open-hole profile.

This paper proposes a Gaussian process regression surrogate model based on the genetic algorithm optimization of swarm intelligence, combined with the Expected Improvement point addition criterion, to optimize and correct the design profile. The flow regulation performance of the optimized V-shaped regulating ball valve is verified through a combination of numerical simulation and experiment.

The results demonstrate that the optimized V-shaped regulating ball valve has higher flow regulation accuracy and a more stable flow regulation process. After optimization, the flow characteristic curve of the spool is closer to the ideal equal percentage characteristic. The simulation results of the flow field are consistent with the experimental results.

The proposed method significantly reduces the optimization time, has higher efficiency and solves the problem that traditional optimization methods struggle with, which is ensuring optimal flow regulation performance. Compared to the traditional trial-and-error optimization method, the proposed method is more effective. The feasibility of the method is supported by experimental results.

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.

The great value of offline identification of machine parameters is when the machine manufacturer does not provide its parameters. Most machine control strategies require parameter values, and some circumstances in the industrial sector only require offline identification. This paper aims to present a new offline method for estimating induction motor parameters based on least squares and a salp swarm algorithm (SSA).

The central concept is to use the classic least squares (LS) method to acquire the majority of induction machine (IM) constant parameters, followed by the SSA method to obtain all parameters and minimize errors.

The obtained results showed that the LS method gives good results in simulation based on the assumption that the measurements are noise-free. However, unlike in simulations, the LS method is unable to accurately identify the machine’s parameters during the experimental test. On the contrary, the SSA method proves higher efficiency and more precision for IM parameter estimation in both simulations and experimental tests.

After performing a primary identification using the technique of least squares, the initial intention of this study was to apply the SSA for the purpose of identifying all of the machine’s parameters and minimizing errors. These two approaches use the same measurement from a simple running test of an IM, and they offer a quick processing time. Therefore, this combined offline strategy provides a reliable model based on the identified parameters.

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

This paper aims to further develop stator permanent magnet (PM) type memory machines by providing generalized design guidelines for double-stator memory machines (DSMMs) with hybrid PMs. This paper discusses the design experience of DSMMs and presents a comparative study of radial magnetization (RM) and circumferential magnetization (CM) types.

It begins with an introduction to RM and CM operating principles and magnetization mechanisms. Then, a comparative study is conducted for one of the RM-DSMM rotor pole pairs, inner and outer stator clamping angles and low coercive force PMs thickness. Finally, the two machines’ finite element simulation performance is compared. The validity of the proposed machine structure is demonstrated.

In this paper, the double-stator structure is extended to parallel hybrid PM memory machines, and two novel DSMMs with RM and CM configurations are proposed. Two types of DSMMs have PMs and magnetizing windings on the inner stator and armature windings on the outer stator. The main difference between the two is the arrangement of PMs on the inner stator.

Conventional stator PM memory machines have geometrical space conflicts between the PM and armature windings. The proposed double-stator structure can alleviate these conflicts and increase the torque density accordingly. In addition, this paper contributes to comparing the arrangement of hybrid PMs for DSMMs.

Considering the influence of deformation error, the target poses must be corrected when compensating for positioning error but the efficiency of existing positioning error compensation algorithms needs to be improved. Therefore, the purpose of this study is to propose a high-efficiency positioning error compensation method to reduce the calculation time.

The corrected target poses are calculated. An improved back propagation (BP) neural network is used to establish the mapping relationship between the original and corrected target poses. After the BP neural network is trained, the corrected target poses can be calculated with short notice on the basis of the pose correction similarity.

Under given conditions, the calculation time when the trained BP neural network is used to predict the corrected target poses is only 1.15 s. Compared with the existing algorithm, this method reduces the calculation time of the target poses from the order of minutes to the order of seconds.

The proposed algorithm is more efficient while maintaining the accuracy of the error compensation.

This method can be used to quickly position the error compensation of a large parallel mechanism.

This study aims to present a modified interleaved boost converter (MIBC) topology for improving the reliability and efficiency of power electronic systems.

The MIBC topology was implemented with two parallel converters, operated with a −180 degree phase shift. Using this methodology, ripples are reduced. The state-space model was analysed with a two-switch MIBC for different modes of operation. The simulation was carried out and validated using a hardware prototype.

The performance of the proposed MIBC shows better output voltage, current and power than the interleaved boost converter (IBC) for the solar PV array. The output power of the proposed converter is 1.353 times higher than that of existing converters, such as boost converter (BC) and IBC. The output power of the four-phase IBC is 30 kW, whereas that of the proposed two-phase MIBC is 40.59 kW. The efficiency of MIBC was better than that of IBC (87.01%). By incorporating interleaved techniques, the total inductor current is reduced by 29.60% compared with the existing converter.

The proposed MIBC can be used in a grid-connected system with an inverter circuit for DC-to-AC conversion, electric vehicle speed control, power factor correction circuit, high-efficiency converters and battery chargers.

The work presented in this paper is a modified version of IBC. This modified MIBC was modelled using the state-space approach. Furthermore, the state-space model of a two-phase MIBC was implemented using a Simulink model, and the same was validated using a hardware setup.

Liquid-assisted laser surface texturing technology was used to create composite microtextures on triangular guide rail surfaces to enhance their tribological properties.

Numerical simulations were used to investigate the impact of various microtextures on fluid dynamic lubrication. Reciprocating friction and wear tests, followed by mechanistic analysis, examined the combined tribological effects of microtextured surfaces and lubricants.

The numerical simulation outcomes reveal a significant augmentation in the influence of fluid dynamic pressure due to composite microtextures, consequently amplifying the load-bearing capacity of the oil film. The average friction coefficient of composite microtextured samples was approximately 0.136 in reciprocating pin-on-disk friction tests, representing approximately 17% decrease compared to polished samples. Triangular guide rails with composite microtextures demonstrated the lowest average coefficient under conditions of high-speed and heavy-loading in the reciprocating friction and wear tests. Additionally, the presence of composite microtextures was found to promote the formation of adsorbed and friction films during friction, potentially contributing to the enhancement of tribological properties.

Triangular guide rails face high friction and wear, limiting their stability in demanding applications like machine tool guideways. This paper proposes a novel approach for steel triangular guide rails, involving composite microtexturing, numerical fluid simulations, liquid-assisted laser surface texturing and friction-wear testing. By implementing composite microtextures, the method aims to reduce friction coefficients and extend guideway service life, thereby saving energy and reducing maintenance costs. Enhancing the antifriction and antiwear properties of machine tool guideways is crucial for improving performance and longevity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0183/

The inclusion of heritage dwellings in the UK decarbonization policies can contribute to cut operational carbon emissions from the building stock; this needs to be made a priority if net zero carbon targets are to be achieved. However, the energy and carbon savings potential of suitable retrofit interventions on this part of the stock is extremely variable and strictly intertwined with the range of baseline conditions of such dwellings. This study aims to propose a framework for interventions in traditional listed dwellings (TLDs) to improve their energy performance utilizing dynamic energy simulation (DES) of selected case studies (CSs) in the city of Brighton and Hove (South-East England).

To achieve this aim, the study established a baseline scenario which provides a basis for the assessment of energy performance and thermo-hygrometric behaviour pre- and post-interventions and allows for comparison between different CSs under comparable conditions.

Presenting a brief overview of the methodology adopted in this study, the paper describes the approach devised to generate such baseline scenario. The paper then compares the results obtained from simulation of normalized and baseline models with the status-quo energy consumption of the dwellings investigated (based on meter readings).

This analysis finally allows to highlight some key physical determinants of the baseline HEC which, in the following stage of research, proved to have a considerable effect also on the amount of energy and carbon savings achievable post retrofit interventions.