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This paper aims to improve the permeability and antifouling of polysulfone (PSF) ultrafiltration membranes, the PSF matrix was modified by incorporating sulfonated polysulfone (SPSF).

Systematic investigations were conducted on the synergistic effects of a pore-forming agent, coagulation bath temperature and SPSF doping in the casting solution on blended ultrafiltration membranes. The chemical composition of the membranes was analyzed using Fourier transform infrared spectroscopy. The morphology and surface roughness of the membranes were characterized using scanning electron microscopy and atomic force microscopy. The hydrophilicity of the membrane surface was analyzed using a contact angle meter. The permeability and antifouling properties of the blended membranes were also investigated through filtration experiments.

The results indicated that the blended ultrafiltration membranes demonstrated an optimal overall performance when PVP-K30 content was 5.0 Wt.%, coagulation bath temperature was 30°C and SPSF content was 2.4 Wt.%. In comparison to a pure PSF ultrafiltration membrane, there was a significant increase in pure water flux (390.7 L·m⁻²·h⁻¹) by 2.2 times, while bovine serum albumin retention slightly decreased to 93.8%. In addition, the flux recovery rate improved by 2.1 times (71.4%) compared to that of the original PSF ultrafiltration membrane.

The method provided a simple and practical solution for improving the antifouling and permeability of PSF ultrafiltration membranes.

SPSF was anticipated to serve as an excellent modification additive for the preparation of ultrafiltration membranes with superior properties.

This study aims to investigate the morphology and physicochemical properties of BiOBr/Polyvinylidene fluoride (PVDF) composite membranes and the differences in the properties of BiOBr/PVDF composite membranes made by adding different precursor ratios during the casting process.

In this paper, sodium bromide and Bi(NO3)3 were used as precursors for the preparation of BiOBr photocatalysts, and PVDF membranes were modified by using the phase conversion method in conjunction with the in situ deposition method to produce BiOBr/PVDF hydrophilic composite membranes with both membrane separation and photocatalytic capabilities.

The characterization results confirmed that the composites were successfully and homogeneously co-mingled in the PVDF membranes. The related performance of the composite membrane was tested, and it was found that the composite membrane with the optimal precursor incorporation ratio had good photocatalytic efficiency and antipollution ability; the removal efficiencies of methyl orange, rhodamine B and methylene blue were 80.43%, 85.02% and 86.94%, respectively, in 2.5 h. The photocatalytic efficiency of composite membranes with different precursor ratios increased and then decreased with the increase of the precursor addition ratio.

The composite membrane is prepared by phase conversion method with in situ deposition method, and the BiOBr material has unique advantages for the degradation of organic dyes. The comprehensive experimental data can be known that the composite membrane prepared in this paper has high degradation efficiency and good durability for organic dyes.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.

This research proposes a viable method of slab and shore load computation for the partial striking technique utilized in high-rise construction projects to optimize the use of horizontal formwork. The proposed Partial Striking Simplified Method (PSSM) is designed to be utilized by industry practitioners to schedule the construction operations of casting floors in order to control the formwork costs incurred throughout the completion of a project.

The article presents the PSSM for calculating slab and shore loads in multi-story building construction. It introduces the concept of “clearing before striking,” where shore supports are partially removed after a few days of pouring fresh concrete. The PSSM procedure is validated through numerical analysis and compared to other simplified approaches. Additionally, a user-friendly Python program based on the PSSM procedure is developed to explore the capability of the PSSM procedure and is used to study the variations in slab load, shoring level, concrete grade and cycle time.

The study successfully developed a more efficient and reliable method for estimating the loads on shores and slabs using partial striking techniques for multi-story building construction. Compared to other simplified approaches, the PSSM procedure is simpler and more precise, as demonstrated through numerical analysis. The mean of shore and slab load ratios are 1.08 and 1.07, respectively, which seems to have a slight standard deviation of 0.29 and 0.21 with 3D numerical analysis. The Python program developed for load estimation is effective in exploring the capability of the proposed PSSM procedure. The Python program's ability to identify the floor under maximum load and determine the specific construction stage provides valuable insights for multi-story construction, enabling informed decision-making and optimization of construction methods.

High-rise construction in Indian cities is booming, though this trend is not shared by all the country's major metropolitan areas. The growing construction sector in urban cities demands rapid construction for efficient utilization of formwork to control the construction costs of project. The proposed procedure is the best option to optimize the formwork construction cost, construction cycle time, the suitable formwork system with optimum cost, concrete grade for the adopted level of shoring in partaking and many more.

The proposed PSSM reduces the calculation complexity of the existing simplified method. This is done by considering the identical slab stiffness and identical shore layout for uniform load distribution throughout the structure. This procedure utilizes a two-step load distribution calculation for clearing phase. Initially, the 66% prop load of highest floor level is distributed uniformly over the lower interconnected slabs. In the second step, the total prop load is removed equally from all slabs below it. This makes the load distribution user-friendly for the industry expert.

The paper aims to provide an efficient dispatching schedule for ready-mix concrete (RMC) trucks and create a balance between batch plants and construction sites.

The paper focused on developing a new metaheuristic swarm intelligence algorithm using Java code. The paper used statistical criterion: mean, standard deviation, running time to verify the effectiveness of the proposed optimization method and compared its derivatives with other algorithms, such as genetic algorithm (GA), Tabu search (TS), bee colony optimization (BCO), ant lion optimizer (ALO), grey wolf optimizer (GWO), dragonfly algorithm (DA) and particle swarm optimization (PSO).

The paper proved that integrating GWO and DA yields better results than independent algorithms and some selected algorithms in the literature. It also suggests that multi-independent batch plants could effectively cooperate in a system to deliver RMC to various construction sites.

The paper provides a compelling new hybrid swarm intelligence algorithm and a model allowing multi-independent batch plants to work in a system to deliver RMC. It fulfills an identified need to study how batch plant managers can expand their dispatching network, increase their competitiveness and improve their supply chain operations.

This study aims to get rid of non-degradable polyvinyl chloride (PVC) waste as well as sunflower seed cake (SSC) waste by preparing eco-friendly composites from both in different proportions to reach good mechanical and insulating properties for antimicrobial and antistatic applications.

Eco-friendly composite films based on waste polyvinylchloride (WPVC) and SSC of concentrations (0, 10, 20, 30 and 40 Wt.%) were prepared using solution casting method. Further, the effect of sunflower seed oil (SSO) on the biophysical properties of the prepared composites is also investigated. Fourier transform infrared spectroscopy, X-ray diffraction (XRD), scanning electron microscope, mechanical, thermal, dielectric properties were assessed. Besides, the antimicrobial and biodegradation tests were also studied.

The crystallinity increases by rising SSC concentration as revealed by XRD results. Additionally, the permittivity (ε′) increases by increasing SSC filler and SSO as well. A remarkable increase in dc conductivity was attained after the addition of SSO. While raw WPVC has very low bacterial activity. The composite films are found to be very effective against staphylococcus epidermidis, staphylococcus aureus bacteria and against candida albicans as well. On the other hand, the weight loss of WPVC increases by adding of SSC and SSO, as disclosed by biodegradation studies.

The study aims to reach the optimum method for safe and beneficial disposal of PVC waste as well as SSC for antistatic and antimicrobial application.

Microwave curing (MC) can facilitate rapid concrete repair in cold climates without using conventional accelerated curing technologies which are environmentally unsustainable. Accelerated curing of concrete under MC can contribute to the decarbonisation of the environment and provide economies in construction in several ways such as reducing construction time, energy efficiency, lower cement content, lower carbonation risk and reducing emissions from equipment.

The paper investigates moisture loss and pore properties of six cement-based proprietary concrete repair materials subjected to MC. The impact of MC on these properties is critically important for its successful implementation in practice and current literature lacks this information. Specimens were microwave cured for 40–45 min to surface temperatures between 39.9 and 44.1 °C. The fast-setting repair material was microwave cured for 15 min to 40.7 °C. MC causes a higher water loss which shows the importance of preventing drying during MC and the following 24 h.

Portland cement-based normal density repair mortars, including materials incorporating pfa and polymer latex, benefit from the thermal effect of MC on hydration, resulting in up to 24% reduction in porosity relative to normal curing. Low density and flowing repair materials suffer an increase in porosity up to 16% due to MC. The moisture loss at the end of MC and after 24h is related to the mix water content and porosity, respectively.

The research on the application of MC for rapid repair of concrete is original. The research was funded by the European commission following a very rigorous and competitive review process which ensured its originality. Original data on the parameters of porosity and moisture loss under MC are provided for different generic cementitious repair materials which have not been studied before. Application of MC to concrete construction especially in cold climates will provide environmental, economic and energy benefits.

The purpose of this study is to prepare a state-of-the-art review on advanced ceramic materials including their fabrication techniques, characteristics, applications and wettability.

This review paper presents the various types of advanced ceramic materials according to their compounding elements, fabrication techniques of advanced ceramic powders as well as their consolidation, their characteristics, applications and wetting properties. Hydrophobic/hydrophilic properties of advanced ceramic materials are described in the paper with their state-of-the-art application areas. Optical properties of fine ceramics with their intrinsic characteristics are also presented within. Special focus is given to the brief description of application-based manipulation of wetting properties of advanced ceramics in the paper.

The study of wetting/hydrophobicity/hydrophilicity of ceramic materials is important by which it can be further modified to achieve the required applications. It also makes some sense that the material should be tested for its wetting properties when it is going to be used in some important applications like biomedical and dental. Also, these advanced ceramics are now often used in the fabrication of filters and membranes to purify liquid/water so the study of wetting characteristics of these materials becomes essential. The optical properties of advanced ceramics are equally making them suitable for many state-of-the-art applications. Dental, medical, imaging and electronics are the few sectors that use advanced ceramics for their optical properties.

This review paper includes various advanced ceramic materials according to their compounding elements, different fabrication techniques of powders and their consolidation, their characteristics, various application area and hydrophobic/hydrophilic properties.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.