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This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

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.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

The aircraft model with delta wing, V-shaped tail and blended wing body is designed, and high-precision unstructured grid technology is used to deal with the surface of air brake and fuselage. The calculation method based on multiple tracking and dynamic scattering is presented to calculate RCS.

The fuselage has a low scattering level, and the opening air brake will bring obvious dynamic RCS effects to itself and the whole machine. The average indicator of air brake RCS can be lower than –0.6 dBm² under the tail azimuth, while that of forward and lateral direction is lower. The mean RCS of fuselage is obviously higher than that of air brake, while the deflected air brake and its cabin can still provide strong scattering sources at some azimuths. When the air brake is opening, the change amplitude of the aircraft forward RCS can exceed 19.81 dBm².

This research has practical significance for the dynamic electromagnetic scattering analysis and stealth design of the air brake.

The calculation method for aircraft RCS considering air brake dynamic deflection has been established.

This paper aims to investigate how different knitted structures affect the illuminative effect of polymeric optical fibres (POFs).

Knit prototypes were constructed using a 7-gauge industrial hand flat knitting machine. The textile prototype swatches developed in this study tested POF illumination in three types of knitting structures: intervallic knit and float stitch structures; POF inlaid into double plain and full cardigan structures; and double plain and partial knitting structures. The illuminative effects of the POFs in seven prototype swatches were analysed and compared.

It is possible to use an industrial hand flat knitting machine to knit POFs. Longer floats expose more POFs, which boosts illumination but limits the textile’s horizontal stretchability. The openness of the full cardigan structure maximises POF exposure and contributes to even illumination. The partial knitting in different sections achieves the most complete physical integration of POFs into the knitted textiles but constrains the horizontal stretchability of the textiles.

The integration of POFs into knitted textiles provides a functional illuminative effect. Applications include but are not limited to fashion, architecture and interior design.

This study is novel, as it investigates new POF knitted textiles with different loop structures. This study examines how knit stitches affect POFs in intervallic knit and float stitch, inlaid POF double knit, double plain and partial knit and the illuminative effects of the knitted textile.

Aluminum alloy is considered an ideal material in aerospace, automobile and other fields because of its lightweight, high specific strength and easy processing. However, low hardness and strength of the surface of aluminum alloys are the main factors that limit their applications. The purpose of this study is to obtain a composite coating with high hardness and lubricating properties by applying GO–PVA over MAO coating.

A pulsed bipolar power supply was used as power supply to prepare the micro-arc oxidation (MAO) coating on 6061 aluminum sample. Then a graphene oxide-polyvinyl alcohol (GO–PVA) composite coating was prepared on MAO coating for subsequent experiments. Samples were characterized by Fourier infrared spectroscopy, X-ray diffraction, Raman spectroscopy and thermogravimetric analysis. The friction test is carried out by the relative movement of the copper ball and the aluminum disk on the friction tester.

Results showed that the friction coefficient of MAO samples was reduced by 80% after treated with GO–PVA composite film.

This research has made a certain contribution to the surface hardness and tribological issues involved in the lightweight design of aluminum alloys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0427/

Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process.

PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles.

PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one.

The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding.

Polymer laser powder bed fusion (PBF-LB/P) is an additive manufacturing technology that is sustainable due to the possibility of recycling the powder multiple times and allowing the fabrication of gears without the aid of support structures and subsequent assembly. However, there are constraints in the process that negatively affect its adoption compared to other additive technologies such as material extrusion to produce gears. This study aims to demonstrate that it is possible to overcome the problems due to the physics of the process to produce accurate mechanism.

Technological aspects such as orientation, wheel-shaft thicknesses and degree of powder recycling were examined. Furthermore, the evolving tooth profile was considered as a design parameter to provide a manufacturability map of gear-based mechanisms.

Results show that there are some differences in the functioning of the gear depending on the type of powder used, 100% virgin or 50% virgin and 50% recycled for five cycles. The application of a groove on a gear produced with 100% virgin powder allows the mechanism to be easily unlocked regardless of the orientation and wheel-shaft thicknesses. The application of a specific evolutionary profile independent of the diameter of the reference circle on vertically oriented gears guarantees rotation continuity while preserving the functionality of the assembled mechanism.

In the literature, there are various studies on material aging and reuse in the PBF-LB/P process, mainly focused on the powder deterioration mechanism, powder fluidity, microstructure and mechanical properties of the parts and process parameters. This study, instead, was focused on the functioning of gears, which represent one of the applications in which this technology can have great success, by analyzing the two main effects that can compromise it: recycled powder and vertical orientation during construction.

This study aimed to review various existing methods for improving the quality of recycled concrete aggregates (RCAs) as a possible substitution for natural aggregates (NAs) in concrete. It is vital as the old paste attached to the RCA weakens its structure. It is due to the porous structure of the RCA with cracks, weakening the interfacial transition zone (ITZ) between the RCA and binding material, negatively impacting the concrete's properties. To this end, various methods for reinforcement of the RCA, cleaning the RCA's old paste and enhancing the quality of the RCA-based concrete without RCA modification are studied in terms of environmental effects, cost and technical matters. Furthermore, this research sought to identify gaps in knowledge and future research directions.

The review of the relevant journal papers revealed that various methods exist for improving the properties of RCAs and RCA-based concrete. A decision matrix was developed and implemented for ranking these techniques based on environmental, economic and technical criteria.

The identified methods for reinforcement of the RCA include accelerated carbonation, bio deposition, soaking in polymer emulsions, soaking in waterproofing admixture, soaking in sodium silicate, soaking in nanoparticles and coating with geopolymer slurry. Moreover, cleaning the RCA's old paste is possible using acid, water, heating, thermal and mechanical treatment, thermo-mechanical and electro-dynamic treatment. Added to these treatment techniques, using RCA in saturated surface dry (SSD) mixing approaches and adding fibres or pozzolana enhance the quality of the RCA-based concrete without RCA modification. The study ranked these techniques based on environmental, economic and technical criteria. Ultimately, adding fibres, pozzolana and coating RCA with geopolymer slurry were introduced as the best techniques based on the nominated criteria.

The study supported the need for better knowledge regarding the existing treatment techniques for RCA improvement. The outcomes of this research offer an understanding of each RCA enrichment technique's importance in environmental, economic and technical criteria.

The practicality of the RCA treatment techniques is based on economic, environmental and technical specifications for rating the existing treatment techniques.