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This study proposes a robust estimation technique for the single-phase grid voltage fundamental frequency under grid disturbances. The technique relies on a demodulation method and a finite-impulse-response-based differentiation filter (DF). A frequency domain analysis for designing the DF is presented and is used to estimate the time-varying fundamental frequency from the instantaneous phase angle obtained by the demodulation method. The technique can reject the negative effects caused by the presence of DC offset and harmonics. The proposed DF shows less sensitivity to the presence of oscillations caused by the demodulation method when compared to a similar finite-impulse-response-based DF. Simulation and experimental results are provided to verify the performance of the proposed technique.

In this study, rolled plates of AA 2198 T3 aluminium alloy are friction-stir welded in butt configuration varying two fundamental process parameters: rotational and welding speeds. Two sets of empirical models based on regression analysis are developed. The first one predicts the stationary values of the in-plane and downwards forging welding forces in dependence of the process parameters under investigation. The second one predicts the mechanical strength, in particular yield and tensile strength, of the friction-stir welded joints as function of the same parameters. For the development of the empirical models, two 3 2 full factorial designs are used: one having the stationary values of the welding forces and the other having the yield and tensile strength as observed responses, respectively. Statistical tools such as analysis of variance, F tests, Mallows’ C P , coefficient of determination etc. are used to build and to validate the developed models. By using the desirability function approach, the optimum process parameters to simultaneously obtain maximum possible yield and tensile strength are found within the investigated range. The developed models can be effectively used to predict the stationary forces and the mechanical proprieties of the joints at 95% confidence level.

The current study on digital factory (DF) meets some problems, such as disconnected manufacturing sites, independent digital models, isolated data, and non-self-controlled applications. In order to move current situation of DFs forward towards smart manufacturing, this paper attempts to present an overview of current digital situation of factories, and propose a systematical framework of cyber-physical integration in factories, with consideration of the concept of digital twin and the theory of manufacturing service. Particularly, the proposed framework includes four key issues, i.e., (a) fully interconnected physical elements integration , (b) faithful-mirrored virtual models integration , (c) all of elements/flows/businesses-covered data fusion , and (d) data-driven and application-oriented services integration . The corresponding implementable solutions of these four key issues are discussed in turn. As a reference, this paper is promising to bridge the gap in factories from current digital situation to smart manufacturing, so as to effectively facilitate their smart production.

Fused filament fabrication (FFF) is a widely used extrusion-based additive manufacturing process due to its low operating cost and available material options. Polylactic acid (PLA) is a bio-based compostable polymer extensively used as a feedstock material in FFF. The application of PLA in engineering and medical applications is limited due to the low thermal stability associated with the polymer. The present work aims to study the effect of thermal annealing on FFF-printed PLA in static and dynamic flexural loading. Response surface methodology (RSM) is chosen as a design of experiment method to study the effect of annealing time and temperature on flexural properties of printed PLA. Annealing is found to be advantageous in increasing the dynamic flexural properties. Improved glass transition temperature, stiffness, thermal stability, and crystallinity are also evident with annealing. However, annealing is found to be detrimental in improving static flexural properties. Considering the desirability function (DF) approach, annealing time and temperature are optimised for measured static and dynamic flexural properties. Samples are further investigated in scanning electron microscope for failure mode and differential scanning calorimetry for crystalline behaviour of annealed PLA. Empirical models are proposed for predicting the flexural behaviour of printed PLA. The current study has shown that the FFF-printed PLA can be tailored to specific application requirements due to its stable characteristics for thermal loading with thermal annealing.

Selecting an appropriate ANN model is crucial for speeding up the process of building performance simulation during the design phase of residential building layouts, particularly when evaluating three or more green performance metrics simultaneously. In this study, daylight, visual, and outdoor thermal metrics were selected as main green performance. To find the suitable ANN model, sensitivity analysis was used to obtain a set of proper parameters applied to the ANN structure. To train the ANN model with a higher predicting accuracy, this paper tested four different scenarios of ANN parameter setups to find some general guidelines about how to set up an ANN model to predict DF, sunlight hours, QuVue and UTCI. The results showed that an ANN model with a combined output variable demonstrated better average prediction accuracy than ANN models with a separated output variable. Having two times the number of training samplings compared to the number of input variables can lead to a high accuracy of prediction. The ideal number of neurons in the hidden layer was approximately 1.5 times the number of input variables. These findings of how to improve the ANN model may provide guidance for modeling an ANN for building performance.

Full-duplex (FD) with simultaneous wireless information and power transfer (SWIPT) in wireless ad hoc networks has received increased attention as a technology for improving spectrum and energy efficiency. This paper studies the outage performance for a SWIPT-based decode-and-forward (DF) FD relaying network consisting of a single-antenna source S, a two-antenna relay R, and a multi-antenna destination D. Specifically, we propose four protocols, namely static time-switching factor with selection combining (STSF-SC), static time-switching factor with maximal ratio combining (STSF-MRC), optimal dynamic time-switching factor with selection combining (ODTSF-SC), and optimal dynamic time-switching factor with maximal ratio combining (ODTSF-MRC) to fully investigate the outage performance of the proposed system. In particular, the optimal time-switching factor from the ODTSF-SC and ODTSF-MRC methods is designed to maximize the total received data at the destination. In this context, we derive exact closed-formed expressions for all schemes in terms of the outage probability (OP). Finally, the Monte Carlo simulations are conducted to corroborate the theoretical analysis’s correctness and the proposed schemes’ effectiveness.

At present, buildings are increasingly being designed with transparent materials, with glass paneling being especially popular as an installation material due to its architectural allure. However, its major drawback is admitting impractical amounts of sunlight into interior spaces. Office buildings with excessive sunlight in indoor areas lead to worker inefficiency. This article studied kinetic façades as means to provide suitable sunlight for interior spaces, integrated with a triple-identity DNA structure, photosynthetic behavior, and the twist, which was divided into generation and evaluation. The generating phase first used an evolutionary engine to produce potential strip patterns. The kinetic façade was subsequently evaluated using the Climate Studio software to validate daylight admission in an indoor space with Leadership in Energy and Environmental Design (LEED) version 4.1 criteria. To analyze the kinetic façade system, the building envelope was divided into four types: glass panel, static façade, rotating façade (the kinetic façade, version 1); an existing kinetic façade that is commonly seen in the market, and twisting façade (the kinetic façade, version 2); the kinetic façade that uses the process to invent the new identity of the façade. In addition, for both the rotating façade and twisting façade, the degrees of simulation were 20, 50, 80, and 100 degrees, in order to ascertain the potential for both façades to the same degree. Comparing all façades receiving the daylight factor (DF) into the space with more or less sunlight resulted in a decreasing order of potential, as follows: entirely glass façade, twisting façade (the kinetic façade, version 2), rotating façade (the kinetic façade, version 1), and static façade. By receiving the daylight factor (DF), the façade moderately and beneficially filtered appropriate amounts of daylight into the working space. The daylight simulation results indicated that the newly designed kinetic façade (version 2) had more potential than other building envelope types in terms of filtering beneficial daylight in indoor areas. This article also experimented with the kinetic façade prototype in an actual situation to test conditional environmental potential. The twisting façade (the kinetic façade, version 2) was explored in the building envelope with varied adaptability to provide sunlight and for private-to-public, public-to-private, or semi-public working areas.

In this study, a demand-contributed load frequency control (LFC) strategy is proposed for frequency stabilization in a solar–wind-based autonomous microgrid system (AMGS). The proposed control framework employs a structurally enhanced version of the classical proportional-integral (PI) controller, augmented with a one plus derivative filter (PI-(1 + DF)) scheme. To optimize the controller parameters, a physics-inspired metaheuristic technique known as the Fick’s Law Optimization (FLO) is implemented. This controller is designed to address the complex dynamics and uncertainties of the AMGS, which comprises renewable sources (solar and wind), conventional diesel engine generator (DEG), and flexible demand-side contributors such as electric vehicles (EVs), heat pumps (HPs), and freezers. Furthermore, realistic nonlinearities like governor dead band (GDB) and generation rate constraints (GRC) are incorporated into the model to ensure practical relevance. Comparative analysis reveals that the FLO-optimized PI-(1 + DF) controller significantly outperforms recent state-of-the-art algorithms such as the Mine Blast Algorithm (MBA) and the Sine Cosine Algorithm (SCA) in terms of settling time, peak overshoot, and various objective functions. Simulation results conducted in MATLAB/Simulink confirm the efficacy and robustness of the proposed approach, successfully maintaining frequency deviation within acceptable limits even under severe disturbances. Furthermore, robustness tests with ± 50% parametric variations demonstrate the controller’s resilience and adaptability in highly uncertain environments. The peak overshoots (Hz) for a ± 50% variation in MG parameters are 0.02, 0.05, and 0.06, while the corresponding undershoots (Hz) are − 0.957, -0.72, and − 0.48. Similarly, for variations in the droop constant (R) the overshoots (Hz) are 0.074, 0.065, and 0.064, and the undershoots (Hz) are − 0.724, -0.725, and − 0.729, respectively.

This study presents an advancement in the manufacturing of large-scale metallic parts through 3D printing, utilizing Wire Arc Additive Manufacturing (WAAM) technology with a proprietary GMAW Dynamic Feed (GMAW DF) power source (MIG-AD). One of the challenges in this process is maintaining the geometry of the part, particularly at the start and end of the weld beads. Three steel walls were fabricated using 1.2-mm ER70S-6 wire, allowing for the comparison of techniques to minimize these deformations. A bidirectional deposition strategy was employed, testing two distinct approaches. The first technique involved maintaining material deposition for 0.5 s at the end of the bead, while the second technique applied the same duration of deposition at the start of the bead, aiming to compensate for the height at these points. Comparisons were made with a control test without applying these techniques. The results of profilometry 3D indicated that maintaining deposition at the end of the bead resulted in greater deformation. In contrast, the technique of maintaining deposition at the start of the bead significantly improved the part’s geometry. Based on this result, it was possible to fabricate a 60-mm high wall without significant deformations.

Ultrafiltration/diafiltration (UF/DF) plays an important role in the manufacturing of biopharmaceuticals. Monitoring critical process parameters and quality attributes by process analytical technology (PAT) during those steps can facilitate process development and assure consistent quality in production processes. In this study, a lab-scale cross-flow filtration (CFF) device was equipped with a variable pathlength (VP) ultraviolet and visible (UV/Vis) spectrometer, a light scattering photometer, and a liquid density sensor (microLDS). Based on the measured signals, the protein concentration, buffer exchange, apparent molecular weight, and hydrodynamic radius were monitored. The setup was tested in three case studies. First, lysozyme was used in an UF/DF run to show the comparability of on-line and off-line measurements. The corresponding correlation coefficients exceeded 0.97. Next, urea-induced changes in protein size of glucose oxidase (GOx) were monitored during two DF steps. Here, correlation coefficients were ≥ 0.92 for static light scattering (SLS) and dynamic light scattering (DLS). The correlation coefficient for the protein concentration was 0.82, possibly due to time-dependent protein precipitation. Finally, a case study was conducted with a monoclonal antibody (mAb) to show the full potential of this setup. Again, off-line and on-line measurements were in good agreement with all correlation coefficients exceeding 0.92. The protein concentration could be monitored in-line in a large range from 3 to 120 g L− 1. A buffer-dependent increase in apparent molecular weight of the mAb was observed during DF, providing interesting supplemental information for process development and stability assessment. In summary, the developed setup provides a powerful testing system for evaluating different UF/DF processes and may be a good starting point to develop process control strategies.