Search Results (75)

Swine wastewater is a high-strength agricultural effluent characterized by high organic loading, elevated ammonium nitrogen and phosphorus concentrations, and frequently low C/N ratios, which make simultaneous pollutant removal and resource recovery challenging. Conventional physicochemical, anaerobic, and aerobic treatment technologies are widely used, but they are often constrained by high energy demand, ammonia inhibition, insufficient nitrogen recovery under low C/N conditions, and limited resource valorization. This review comparatively evaluates these conventional technologies alongside microalgal and algal–bacterial symbiotic (ABS) systems for swine wastewater treatment and resource recovery. Particular attention is given to algal–bacterial interactions, oxygen and carbon exchange, nitrogen and phosphorus removal pathways, reactor configurations, key operational parameters, and biomass valorization routes. The reviewed evidence shows that conventional anaerobic–aerobic systems generally achieve stable COD removal (>80%) but often provide limited nitrogen recovery, whereas microalgal systems can remove 80–90% of nitrogen and phosphorus but remain restricted by ammonia toxicity, light attenuation, and biomass harvesting costs. Under optimized conditions, ABS granular systems have achieved >90% COD removal, >80% total nitrogen removal, and 70–95% total phosphorus removal, while also improving biomass settleability and process stability. Overall, ABS systems offer a promising route to shift swine wastewater treatment from discharge-oriented pollution control toward resource-oriented management. Future research should prioritize reactor scale-up, long-term operational stability, biological monitoring, and economically viable biomass valorization. Full article

The increasing demand for sustainable materials has accelerated the development of environmentally friendly filaments for fused deposition modeling (FDM). In this study, the surface roughness and thermal degradation behavior of sustainable PLA-based filaments, including PLA, recycled PLA (Re–PLA), and wood-filled PLA (Wood–PLA), were systematically investigated under different FDM printing conditions. A full factorial experimental design was employed to identify the dominant processing parameters and optimize surface quality. Surface roughness was evaluated using values Ra, Rz, and Rq parameters measured on three different surface orientations (top surface at 0°, top surface at 45°, and side surface). Scanning electron microscopy (SEM) was used to examine the relationship between roughness measurements and surface morphology, while thermogravimetric analysis (TGA) was performed to evaluate the thermal degradation behavior of the filaments in relation to printing temperature. The results have shown that filament material is the most important parameter affecting surface roughness. While Wood–PLA exhibited the highest roughness due to fiber-induced surface heterogeneity, recycled Re–PLA showed moderate surface irregularities resulting from degradation compared to pure PLA. Despite a rougher filament surface prior to production, recycled PLA exhibited a surface morphology similar to that of pure PLA after printing, influenced by the processing parameters. Furthermore, SEM findings indicated that the Ra parameter predominantly reflects macro-scale surface topography, while local microstructural heterogeneity can be better characterized by complementary roughness parameters such as Rz. These findings support optimizing printing conditions to improve surface quality and more widespread use of sustainable FDM filaments in applications where surface roughness is critical. Full article

Increasing demands for improved energy efficiency and resource recovery in wastewater management have driven intensified research on microalgal–bacterial consortia (M-BC). This technological approach represents one of the most promising and continuously evolving concepts for integrated wastewater treatment and energy recovery. M-BC systems exploit complementary processes, including photosynthesis, oxygen production, nutrient uptake by microalgae, as well as heterotrophic degradation of organic contaminants and CO₂ generation by bacteria. Laboratory- and pilot-scale studies demonstrate that such integration can substantially reduce energy demand while significantly improving technological performance. Metabolic synergy, metabolite exchange, intercellular communication, and the specific aggregate architecture collectively determine the stability and high productivity of these consortia. Depending on operational conditions, M-BC may occur as suspended cultures, biofilm-based systems, or granules, which differ in process characteristics and biomass recovery potential. Available evidence indicates that M-BC biomass can serve as a highly efficient substrate for anaerobic digestion (AD). The methane production potential of M-BC reaches 350–365 mL CH₄/gVS, and following pretreatment may increase to 530–560 mL CH₄/gVS, exceeding typical ranges reported for conventional sewage sludge. These values were obtained under specific process conditions and depend on biomass characteristics, consortium structure, inoculum type, and operational parameters; therefore, their generalisation should be interpreted with caution. However, practical implementation remains constrained by process-related barriers directly affecting AD performance, including extracellular polymeric substance (EPS)-mediated hydrolysis limitation and nitrogen-associated inhibition linked to low C/N ratios and ammonia accumulation. Additional challenges include seasonal variability in biomass composition and incomplete understanding of M-BC behaviour under anaerobic conditions, particularly at scale. This paper provides a comprehensive and integrative analysis of the structure and biochemistry of M-BC biomass, their ecological mechanisms, technological configurations, and current knowledge regarding their susceptibility to anaerobic digestion. The review identifies the key biological, chemical, and process-related barriers and highlights research directions required for future integration of M-BC into circular wastewater treatment systems and energy-oriented biomass valorisation. Full article

Wire–Laser Additive Manufacturing (WLAM) is a promising directed energy deposition technique for producing and repairing high-performance components with high material efficiency and strong metallurgical bonding. This study optimizes single-track Inconel 718 claddings deposited by WLAM on AISI 304L stainless steel and S355 structural steel substrates, focusing on the relationships between processing parameters, microstructure, post-deposition heat treatment, and mechanical performance. A systematic parametric assessment evaluated the influence of laser power, laser speed, wire feed rate, and shielding gas pressure on key quality metrics, including dilution, wettability, porosity, and cracking. Distinct optimal processing windows were identified for each substrate, reflecting their different thermal responses: for 304L, 8.5 kW laser power, 0.55 m/min laser speed, 5 m/min wire feed rate, and 2 bar argon; for S355, 9.6 kW laser power, 0.6 m/min laser speed, 4.9 m/min wire feed rate, and 4 bar argon. Post-deposition heat treatment markedly enhanced performance by dissolving Nb-rich interdendritic Laves phase and promoting γ′/γ″ precipitation. As a result, clad hardness increased from ≈225 HV 0.3 (as-built) to ≈412 H V0.3 after heat treatment (+84%). Tensile testing confirmed substantial strengthening, with yield strength increasing from 447 to 853 MPa (horizontal build) and from 488 to 960 MPa (vertical), while ultimate tensile strength rose from 824 to 1057 MPa (horizontal) and from 836 to 1090 MPa (vertical). Mechanical anisotropy remained significant, linked to columnar grain morphology and build orientation. Overall, the results provide practical process window and heat treatment guidelines for reliable industrial implementation of high-quality Inconel 718 claddings on steel substrates for demanding applications. Full article

Against the backdrop of the continuous advancement of high-quality development in road infrastructure and the growing demand for waste asphalt recycling, the application limitations of traditional petroleum-based asphalt rejuvenators have become increasingly prominent due to their high resource dependence, poor compatibility with aged asphalt, and high volatility. By contrast, bio-oil, characterized by wide feedstock availability, outstanding renewability, and the inherent potential to modulate the colloidal structure and properties of aged asphalt, has gradually emerged as a critical research direction in the field of asphalt rejuvenator development. This paper provides a comprehensive review on the research, development and engineering application of bio-based rejuvenators. Firstly, the main feedstock systems, including vegetable oils, lignin derivatives and algal oils, are introduced, and the core preparation technologies (e.g., pyrolysis and alkali-catalyzed transesterification) are discussed, along with the impacts of their key process parameters on the chemical composition and storage stability of the end products. Subsequently, the performance of various bio-based rejuvenators in optimizing the rheological properties, high- and low-temperature performance, as well as fatigue and cracking resistance of aged asphalt is summarized, and the underlying rejuvenation mechanisms are generalized. Finally, the prevailing technical bottlenecks, such as inconsistent quality of as-prepared products and insufficient understanding of the long-term aging mechanism, are analyzed. Future research directions including oriented molecular modification, interfacial regulation, and full life cycle assessment (LCA) are proposed, to provide a systematic reference for their large-scale engineering application. Full article

Urban blue spaces, including rivers, lakes, and ponds, are increasingly recognized as nature-based solutions for mitigating the Urban Heat Island (UHI) effect. However, fragmented evidence and inconsistent evaluation frameworks have limited their effective integration into climate-adaptive urban planning. This study conducts a comprehensive bibliometric analysis and systematic review to synthesize current knowledge on the cooling effects of urban blue spaces. A total of 110 peer-reviewed publications published between 2015 and 2025 were retrieved from the Web of Science Core Collection and analyzed using the Bibliometric-Systematic Literature Review (B-SLR) framework. The results reveal a rapidly growing research field characterized by increasing interdisciplinary integration. Evidence consistently indicates that the cooling effects of blue spaces exhibit pronounced diurnal and seasonal variability, highlighting a “diurnal paradox” of daytime cooling versus nighttime warming risks, with stronger impacts in summer than in winter. Cooling performance is governed by non-linear morphological thresholds regarding size, shape, spatial configuration, and upwind location, where aerodynamic ventilation is critical for extending the cooling range. Moreover, the interaction between blue spaces, building morphology (gray infrastructure), and green infrastructure plays a decisive role: specific density thresholds in built environments can constrain cooling diffusion, whereas synergistic blue–green integration significantly enhances thermal regulation through coupled evaporative, shading, and ventilation processes. Overall, this review demonstrates a clear shift from isolated temperature-based assessments toward systemic, planning-oriented approaches emphasizing multi-scale integration and context-sensitive design. The findings provide operational parameters and demand-based strategies for optimizing blue infrastructure in climate-resilient urban planning. Full article

The rapid development of digital manufacturing and robotic systems places increased demands on the accuracy and reliability of industrial manipulators. Traditional time-based reliability metrics do not reflect the robot’s ability to consistently achieve the desired position and orientation within process tolerances or the probability of the end-effector falling into a given area of permissible poses. The proposed framework integrates a deterministic kinematic model, a stochastic representation of Denavit–Hartenberg parameters and control variables, analytical methods for estimating probabilities, and numerical modeling using the Monte Carlo method. The methodology has been tested on the widely used industrial robot FANUC LR Mate 200iD/7L. The results demonstrate a significant dependence of geometric reliability on the kinematic configuration of the manipulator, with maximum reliability in compact poses and a significant reduction in elongated configurations near singularities. Comprehensive validation was carried out, including numerical experiments on a planar prototype, high-precision physical measurements on a real robot and analysis of operational data, which confirmed the adequacy of the proposed model. The developed approach provides a powerful tool for designing, optimizing and predicting the reliability of robotic cells in high-precision automation environments. Full article

Mission-oriented supply chains involve multi-phase tasks, strong resource interdependencies, and stringent reliability requirements, which make demand planning complex and uncertain. This study develops a structured demand modeling framework to support multi-phase mission-oriented supply chains under budget and reliability constraints by integrating digital twin technology with an adaptive inertia weight particle swarm optimization (AIW-PSO) algorithm. The supply support process is decomposed into four sequential phases—storage, transportation, preparation, and execution—and phase-specific demand models are constructed based on system reliability theory, explicitly incorporating redundancy, maintainability, and repairability. In this work, digital twin technology functions as a data acquisition and virtual experimentation layer that supports parameter calibration, state-aware scenario simulation, and event-triggered re-optimization rather than continuous real-time control. Physical-state updates are mapped to model parameters such as phase durations, failure rates, repair rates, and instantaneous availability, after which the integrated optimization model is re-solved using a warm-start strategy to generate updated demand plans. The resulting multi-phase demand optimization problem is solved using AIW-PSO to enhance global search performance and mitigate premature convergence. The proposed method is validated using a representative mission-oriented supply support scenario with operational and simulated data. Simulation results demonstrate that, under identical budget constraints, the proposed approach achieves higher mission completion capability than conventional PSO-based methods, providing effective and practical decision support for multi-phase mission-oriented supply chain planning. Full article

The surge in demand for patient-specific orthopedic implants necessitates the precise optimization of design and processing parameters for artificial trabecular bone. This research utilizes Voronoi-based porous structures to replicate the irregular geometry characteristic of natural trabecular bone. All specimens were fabricated through fused deposition modeling (FDM) with polylactic acid (PLA). The study systematically investigated the influence of four primary parameters, namely build orientation, extruder temperature, layer height, and pore count, on compressive strength. To ensure experimental efficiency, the research implemented a Taguchi L20 orthogonal array. Subsequent signal-to-noise (S/N) ratio analysis identified the optimal parameter set as a y-90° build orientation, an extruder temperature of 200 °C, a layer height of 0.2 mm, and a count of 150 pores. These findings underscore the necessity of integrated geometric and process parameter optimization to advance additive manufacturing for orthopedic applications. Full article

This review provides an in-depth look at the key process limitations and (structural) defects encountered in the production of polymer films via film blowing extrusion technology. Film blowing is the most widely used method for producing plastic films across various industries, with its increasing demand driven by flexible packaging needs. Overcoming the challenges of this complex production process is essential for ensuring high quality and meeting the growing demand for modern applications, taking into account polymer circularity. In the first part of this paper, the focus is on conventional films, generally polyolefin single-layer films. Common defects such as bubble instability, gauge variations, wrinkles, melt fractures, optical defects, blocking, and surface imperfections like fish eyes are discussed. The most important causes behind these issues are elaborated on, including various molecular and processing parameters, with this paper also offering practical mitigating strategies. In the second part, the specific process limitations and defect types associated with emerging sustainable film technology are focused on, covering films made from recycled materials, biodegradable polymers, polymer blends, and multilayer and machine-direction oriented (MDO) films. While these innovative films offer significant advantages in terms of sustainability and property enhancement, they also present additional points of attention. Also, effective mitigation strategies for addressing these technical issues are incorporated. Overall, this study provides a comprehensive review of film blowing defects, contributing to improved process control, reduced waste, and the production of high-quality films that meet modern requirements. By identifying the root causes of common defects and discussing viable solutions, this review plays a key role in advancing the efficiency, consistency, and sustainability of film blowing technology by presenting a combined experimental and modelling approach that can be used in future work. Full article

Lilium is one of the most valuable cut flowers in the world. Today, due to the global water crisis, the agricultural challenge is to modify cultivation patterns to reduce water requirements by plants. This research was conducted to optimize soilless cultivation systems and nutritional demands to improve morpho-physiological parameters of Oriental × Trumpet (Orienpet; OT) hybrid lily. Four soilless cultivation systems (aeroponic, ultrasonic, hydroponic in pots, and hydroponic in containers) were evaluated using three nutrient solutions (NS1, NS2, NS3), considering two variables: the ratio of ammonium to total nitrogen (0.1, 0.15, and 0.2) and the ratio of calcium to total cations (0.3, 0.5, and 0.7). A factorial experiment was used, arranged as a randomized complete block design. Plants grown in the hydroponic (pot) system treated with nutrient solution NS1 showed favorable and consistent results. Additionally, results revealed that the amount of malondialdehyde and, accordingly, the aging process were lower in the bulbs treated by NS3. Therefore, in addition to NS1, NS3 is also recommended for lily cultivation in the hydroponic (pot) system. Considering that photosynthetic performance improved with increasing ammonium in the nutrient solution of the ultrasonic system, it seems that the lily is an ammonium-feeding plant. However, this issue requires further evaluation. Full article

Ni/ZrO₂ composite coatings are increasingly employed, yet the influence of organic additives under a pulse current regime on their electrodeposition remains insufficiently addressed. This study investigates the combined effect of pulse frequency (0.01–100 Hz) and coumarin concentration (0–2 mmol L⁻¹) on the co-deposition behavior, microstructure, and properties of Ni/ZrO₂ coatings electrodeposited from a Watts-type bath. The structural, morphological, and compositional features were analyzed through SEM/EDS, FE-SEM, and XRD, while microhardness and surface roughness were determined to establish processing–structure–property correlations. The results revealed that coumarin acts as an effective levelling agent, promoting smoother and finer-grained coatings while modifying ZrO₂ incorporation and Ni crystallographic orientation. Increasing coumarin concentration led to a notable refinement of nickel crystallites and a rise in hardness, reaching values close to 650 HV under optimal PC conditions. Pulse frequency was found to strongly influence the microstructural characteristics and particle co-deposition rates, particularly at low frequencies, where a balance between additive adsorption and current modulation favored particle incorporation and enhanced the microhardness. It was demonstrated that the synergistic control of pulse parameters and coumarin concentration enables the design of Ni/ZrO₂ composite coatings with tailored microstructure, low roughness, and superior hardness for demanding applications. Full article

Magnetic confinement nuclear fusion offers a promising solution to the world’s growing energy demands. The DEMO reactor presented here aims to bridge the gap between laboratory fusion experiments and practical electricity generation, posing unique challenges for magnetic plasma diagnostics due to limited space for diagnostic equipment. This study employs Bayesian inference and Gaussian process modeling to integrate data from pick-up coils, flux loops, and saddle coils, enabling a qualitative estimation of the plasma current density distribution relying on only external magnetic measurements. The methodology successfully infers total plasma current, plasma centroid position, and six plasma–wall gap positions, while adhering to DEMO’s stringent accuracy standards. Additionally, the interchangeability between normal pick-up coils and saddle coils was assessed, revealing a clear preference for saddle coils. Initial steps were taken to utilize Bayesian experimental design for optimizing the orientation (normal or tangential) of pick-up coils within DEMO’s design constraints to improve the diagnostic setup’s inference precision. Our approach indicates the feasibility of Bayesian integrated data analysis in achieving precise and accurate probability distributions of plasma parameter crucial for the successful operation of DEMO. Full article

The growing demand from the automotive industry for lightweight, high-performance, and advanced manufacturing techniques for efficient and cost-effective production has accelerated the adoption of fiber-reinforced polymer composites. However, considering the manufacturing complexity of these materials, design remains challenging due to the intricate and interdependent relationships between the process conditions, the part geometry, and the resulting microstructure and quality. This research utilized the Autodesk Moldflow Insight software to design an injection molding process for the manufacturing of discontinuous glass fiber-reinforced polymer parts through computer modeling. A geometrically complex car fender was used as a case study. The effects of various process parameters, particularly gate locations, on the injection-molded parts’ properties (such as the fiber orientation, volumetric shrinkage, and shear rate) were investigated. Multiple injection molding process configurations were designed and simulated, including three, four, and five gates at varying locations. Based on the optimal performance (i.e., low shrinkage, a consistent fiber orientation, and a controllable shear rate), an optimal configuration with four gates at appropriate locations (corresponding to the second gate location set) was identified based on multicriteria decision-making analysis, i.e., volumetric shrinkage of ${8.5}_{-2.2}^{+1.4}\%$, a fiber orientation tensor of 0.927 ± 0.011, and a stable shear rate < 74,324 (1/s). A reduced strain closure model (modified Folgar–Tucker model) was used to predict the glass fiber orientation. A multicriteria decision-making technique, based on similarity ranking with an ideal solution, was employed to optimize the gate location. The simulation results clearly demonstrate that the gate placement is crucial for material behavior during molding and for reducing common defects. The simulation-based injection molding process design for the manufacturing of discontinuous fiber-reinforced polymer parts proposed in this paper can improve the production efficiency, reduce trial-and-error rates, and improve part quality. Full article

The use phase of clothing contributes significantly to the overall environmental impacts due to clothing care practices. Decreasing environmental impact while maintaining washing performance in the use phase can be an effective strategy for sustainability and circularity in the textile value chain. However, existing studies on the environmental impacts of use phase usually consider limited washing conditions and neglect their impacts on washing efficiency. This study proposes a research framework that integrates the Response Surface Methodology (RSM) and Life Cycle Assessment (LCA) methodology to optimize washing parameters for better washing efficiency with less environmental impact in the clothing use phase. A series of laundry experiments were conducted to simulate household laundry, and an environmental impact assessment was conducted based on the experimental data. The optimized washing parameters were explored under eight impact categories and in terms of washing efficiency, and comparative analyses were conducted between three different washing scenarios. The results indicated that input load is the most significant factor influencing both washing efficiency and environmental impact, but with a negative correlation. The optimized washing conditions provided effective trade-offs, demonstrating notable environmental benefits through the scenario study. In the daily washing scenario with an expectation for a middle level of washing efficiency, using the optimized washing conditions can reduce the environmental impact by 80% on average compared to the high-washing-efficiency-oriented washing process and 60% on average compared to the low-environmental-impact-oriented washing process. However, for high washing efficiency demand, optimized washing conditions are less competitive due to increased washing time and detergent use. The results emphasized the importance of choosing appropriate washing parameters according to the demand for washing efficiency. Consistent environmental improvements can be achieved by changing consumer washing habits. Full article