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The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.

Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.

The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.

Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

This paper aims to deal with the design optimization of a synchronous reluctance machine to be used in an X-ray tube, where the goal is to maximize the torque while keeping low the amount of material used, by means of gradient-based free-form shape optimization.

The presented approach is based on the mathematical concept of shape derivatives and allows to obtain new motor designs without the need to introduce a geometric parametrization. This paper presents an extension of a standard gradient-based free-form shape optimization algorithm to the case of multiple objective functions by determining updates, which represent a descent of all involved criteria. Moreover, this paper illustrates a way to obtain an approximate Pareto front.

The presented method allows to obtain optimal designs of arbitrary, non-parametric shape with very low computational cost. This paper validates the results by comparing them to a parametric geometry optimization in JMAG by means of a stochastic optimization algorithm. While the obtained designs are of similar shape, the computational time used by the gradient-based algorithm is in the order of minutes, compared to several hours taken by the stochastic optimization algorithm.

This paper applies the presented gradient-based multi-objective optimization algorithm in the context of free-form shape optimization using the mathematical concept of shape derivatives. The authors obtain a set of Pareto-optimal designs, each of which is a shape that is not represented by a fixed set of parameters. To the best of the authors’ knowledge, this approach to multi-objective free-form shape optimization is novel in the context of electric machines.

The purpose of this paper is to investigate the benefit of pre-emptive disruption management measures for assembly systems towards the target dimension adherence to delivery times.

The research was conducted by creating simulation models for typical assembly systems and measuring its varying throughput times due to changes in their disruption profiles. Due to the variability of assembly systems, key influence factors were investigated and used as a foundation for the simulation setup. Additionally, a disruption profile for each simulated process was developed, using the established disruption categories material, information and capacity. The categories are described by statistical distributions, defining the interval between the disruptions and the disruption duration. By a statistical experiment plan, the effect of a reduced disruption potential onto the throughput time was investigated.

Pre-emptive disruption management is beneficial, but its benefit depends on the operated assembly system and its organisation form, such as line or group assembly. Measures have on average a higher beneficial impact on group assemblies than on line assemblies. Furthermore, it was proven that the benefit, in form of better adherence to delivery times, per reduced disruption potential has a declining character and approximates a distinct maximum.

Characterising the benefit of pre-emptive disruption management measures enables managers to use this concept in their daily production to minimise overall costs. Despite the hardly predictable influence of pre-emptive disruption measures, these research results can be implemented into a heuristic for efficiently choosing these measures.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

This study aims to analyse the non-linear losses of a porous media (stack) composed by parallel plates and inserted in a resonator tube in oscillatory flows by proposing numerical correlations between pressure gradient and velocity.

The numerical correlations origin from computational fluid dynamics simulations, conducted at the microscopic scale, in which three fluid channels representing the porous media are taken into account. More specifically, for a specific frequency and stack porosity, the oscillating pressure input is varied, and the velocity and the pressure-drop are post-processed in the frequency domain (Fast Fourier Transform analysis).

It emerges that the viscous component of pressure drop follows a quadratic trend with respect to velocity inside the stack, while the inertial component is linear also at high-velocity regimes. Furthermore, the non-linear coefficient b of the correlation ax + bx² (related to the Forchheimer coefficient) is discovered to be dependent on frequency. The largest value of the b is found at low frequencies as the fluid particle displacement is comparable to the stack length. Furthermore, the lower the porosity the higher the Forchheimer term because the velocity gradients at the stack geometrical discontinuities are more pronounced.

The main novelty of this work is that, for the first time, non-linear losses of a parallel plate stack are investigated from a macroscopic point of view and summarised into a non-linear correlation, similar to the steady-state and well-known Darcy–Forchheimer law. The main difference is that it considers the frequency dependence of both Darcy and Forchheimer terms. The results can be used to enhance the analysis and design of thermoacoustic devices, which use the kind of stacks studied in the present work.

This article introduces the Special Issue on Sustainable Management of Heritage Buildings in long-term perspective.

It starts by reviewing the gaps in knowledge and practice which led to the creation and implementation of the research project SyMBoL—Sustainable Management of Heritage Buildings in long-term perspective funded by the Norwegian Research Council over the 2018–2022 period. The SyMBoL project is the motivation at the base of this special issue.

The editorial paper briefly presents the main outcomes of SyMBoL. It then reviews the contributions to the Special Issue, focussing on the connection or differentiation with SyMBoL and on multidisciplinary findings that address some of the initial referred gaps.

The article shortly summarizes topics related to sustainable preservation of heritage buildings in time of reduced resources, energy crisis and impacts of natural hazards and global warming. Finally, it highlights future research directions targeted to overcome, or partially mitigate, the above-mentioned challenges, for example, taking advantage of no sestructive techniques interoperability, heritage building information modelling and digital twin models, and machine learning and risk assessment algorithms.

The paper aims to investigate the comfort-related performances of an innovative solar shading solution based on a new composite patented material that consists of a cement-based matrix coupled with a stretchable three-dimensional textile. The paper’s aim is, through a performance-based generative design approach, to develop a high-performance static shading system able to guarantee adequate daylit spaces, a connection with the outdoors and a glare-free environment in the view of a holistic and occupant-centric daylight assessment.

The paper describes the design and simulation process of a complex static shading system for digital manufacturing purposes. Initially, the optical material properties were characterized to calibrate radiance-based simulations. The developed models were then implemented in a multi-objective genetic optimization algorithm to improve the shading geometries, and their performance was assessed and compared with traditional external louvres and overhangs.

The system developed demonstrates, for a reference office space located in Milan (Italy), the potential of increasing useful daylight illuminance by 35% with a reduced glare of up to 70%–80% while providing better uniformity and connection with the outdoors as a result of a topological optimization of the shape and position of the openings.

The paper presents the innovative nature of a new composite material that, coupled with the proposed performance-based optimization process, enables the fabrication of optimized shading/cladding surfaces with complex geometries whose formability does not require ad hoc formworks, making the process fast and economic.

Small highly saturated interior permanent magnet- synchronous machines (IPMSMs) show a very nonlinear behaviour. Such machines are mostly controlled with a closed-loop cascade control, which is based on a d-q two-axis dynamic model with constant concentrated parameters to calculate the control parameters. This paper aims to present the identification of a complete current- and rotor position-dependent d-q dynamic model, which is derived by using a finite element method (FEM) simulation. The machine’s constant parameters are determined for an operation on the maximum torque per ampere (MTPA) curve. The obtained MTPA control performance was evaluated on the complete FEM-based nonlinear d-q model.

A FEM model was used to determine the nonlinear properties of the complete d-q dynamic model of the IPMSM. Furthermore, a fitting procedure based on the nonlinear MTPA curve is proposed to determine adequate constant parameters for MTPA operation of the IPMSM.

The current-dependent d-q dynamic model of the machine models the relevant dynamic behaviour of the complete current- and rotor position-dependent FEM-based d-q dynamic model. The most adequate control response was achieved while using the constant parameters fitted to the nonlinear MTPA curve by using the proposed method.

The effect on the motor’s steady-state and dynamic behaviour of differently complex d-q dynamic models was evaluated. A workflow to obtain constant set of parameters for the decoupled operation in the MTPA region was developed and their effect on the control response was analysed.

This paper aims to identify the impacts of wire and arc additive manufacturing (WAAM) technology on the green supply chain management (GSCM) performance. Also, it intends to identify the most essential WAAM capabilities.

An exploratory case study related to a metallurgical company using WAAM technology to repair metallic components was developed. A research framework to identify WAAM production capabilities and the different GSCM performance criteria was proposed based on the current state of the art. Primary qualitative data provided evidence for developing seven propositions relating WAAM capabilities to GSCM performance.

The paper provides empirical evidence relating to how WAAM production capabilities impact the different performance criteria of the GSCM performance. The results show that “relative advantage” and “supply-side benefits” are critical capabilities developed through WAAM. Furthermore, most of the capabilities regarding “relative advantage” and “supply-side benefits” promote a higher GSCM performance.

This research was carried out using a single case study research design and using qualitative data. Thus, future works are encouraged to test the propositions empirically using quantitative methodologies.

The case study findings support that most WAAM production capabilities promote a higher GSCM performance. Managers could use this research to understand the capabilities developed by this fusion-based additive manufacturing (AM), become aware of the implications of new technology adoption on the supply chain environmental externalities, and develop new business models based on the WAAM capabilities.

This research contributes to expanding the state-of-the art related to WAAM technology by evidencing the relationship between adopting this fusion-based AM technology and green supply chain practices. Also, it provides a set of seven propositions that could be used to theorise the impacts of WAAM adoption on the GSCM performance.

Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.