Search Results (52)

This study highlights waste bread (WB) as a novel, cost-effective, and nutrient-rich substrate for microbial growth, offering a sustainable alternative to conventional media. As a renewable resource, WB promotes the circular economy by reducing food waste and encouraging biotechnological innovation. The incorporation of WB into microbial culture media enhanced the growth of various reference strains (E. coli, E. faecalis, P. aeruginosa, and S. aureus), with at least a two-fold increase compared to conventional Luria-Bertani (LB) medium. Moreover, combining 2% WB with diluted LB (1/10) reduced medium costs by up to 90%. Furthermore, it was confirmed that 1% WB can effectively replace starch during the screening of amylolytic strains. Applying a fractional factorial design, the production of amylase by Bacillus sp. BSS (Amy-BSS) was enhanced 15-fold. An analysis of the Pareto diagram revealed that WB was the most significant factor. Additionally, Amy-BSS was applied to hydrolyze polysaccharides in WB, enabling the generation of high-value-added products in food processing. This hydrolysis process yielded 4.6 g/L of fermentable sugars from 1% WB. Evaluating the economic feasibility of WB valorization into value-added products elucidates potential pathways for cost reduction and enhanced environmental sustainability, thereby positioning WB as a viable tool for sustainable development. Full article

This paper presents a methodology for optimizing an aeronautical propeller to minimize power consumption. A multi-objective approach using blade element momentum (BEM) theory and evolutionary algorithms is employed to optimize propeller design by minimizing power consumption during takeoff and top-of-climb. Three different evolutionary algorithms generated a Pareto front, from which the optimal propeller design is selected. The selected propeller design is evaluated under optimal operational conditions for a specific mission. In this context, two operational approaches for the optimized propellers during flight missions are evaluated. The first approach considers the possibility of only three values for the propeller rotation, while the second allows continuous changes in the rotational speed and pitch angle values, known as the multi-rotational-speed approach. In the second approach, a modal analysis of the propeller is performed using rotating beam theory. The natural frequencies of vibration, constrained by the Campbell diagram, enable an operational analysis and ensure structural integrity by preventing resonance between propeller blades and the rotational procedures. The multi-rotational approach is conducted with and without frequency constraints, resulting in general flight energy reductions of 1.40% and 1.47%, respectively. However, substantial power savings are achieved, namely up to $10\%$ during critical flight states, which can have a significant impact on future engine design and operability. The main contributions of the research lie in analyzing the multi-rotational approach with vibrational constraints of the optimized propeller. This research advances sustainable aviation practices by focusing on reducing power consumption while maintaining performance. Full article

This study presents a novel integrated framework for the structural analysis and optimization of multi-floor buildings by combining validated theoretical models with machine learning and evolutionary algorithms. The proposed Process–Action–Response System (PARS-Solution) accurately computes key structural responses—such as deformations, shear forces, and bending moments—based on eleven critical design parameters ($P_1$ to $P_{11}$). The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achieving an average error of less than 2% in multi-variable prediction scenarios. The results were compared against reference calculations and ETABS simulations to validate its effectiveness, demonstrating deviations of less than 3%. The methodology combines MATLAB-based coding, interpolation from verified reference diagrams, and iterative stiffness adjustment across floors, offering transparency and accuracy. Optimization is performed using Multi-Objective Particle Swarm Optimization (MOPSO), enabling efficient exploration of Pareto-optimal solutions that balance deformation and material usage. Extensive parametric studies reveal the dominant impact of core wall dimensions and floor number on structural efficiency, while the application of stiffness reduction factors (e.g., $P_{11}$) proves effective in reducing material without compromising performance. This hybrid approach enables the delegation of labor-intensive calculations to a trained ANFIS model and supports rapid pre-validation of structural configurations in early design phases. As such, the framework offers a powerful data-driven tool for engineers seeking optimal, lightweight, and high-performance solutions in high-rise building design. Full article

With the impacts of climate change, floods have become increasingly frequent in recent years. Estimating flood hazard thresholds and peak floodwater levels based on flood frequency analysis is crucial for anticipating and preparing for potential flooding events. This study aims to estimate flood hazard thresholds, flood occurrence probabilities, and the return periods of peak floodwater levels in the Nokoue lake watershed in Benin. To achieve this, the standardized water level index, also known as the Flood hazard Index, was calculated to estimate flood hazard thresholds. The three best probability distribution models, Gumbel, Generalized Extreme Value (GEV), and Generalized Pareto (GPA), were selected to project future floodwater levels using annual maximum daily water level data for extreme floods from 1997 to 2022, obtained from a water gauge site at Nokoue lake. Three goodness-of-fit tests were applied to identify the best-fitting probability distribution model: a Taylor diagram (three-dimensional analysis), a cumulative probability density diagram based on the root-mean-square error (RMSE), and an L-moment diagram (two-dimensional analysis). The Flood hazard Index values ranged from −1.10 to +3.40, with 77.78% showing positive indices and 22.22% showing negative indices. The flood hazard thresholds were classified in ascending order of index values: limited hazards, moderate hazards, significant hazards, and critical hazards. The analysis results indicate that the flood hazard thresholds are defined as follows: below 3.94 m for limited hazards, from 3.94 m up to 4.04 m for moderate hazards, from 4.04 m to 4.14 m for significant hazards, and above 4.14 m for critical hazards. The distribution model analysis showed that the Gumbel distribution best fits the Nokoue lake watershed, with an RMSE of 0.0724, compared to 0.0754 and 0.0761 for the GEV and GPA models, respectively. The annual maximum daily water levels for various non-exhaustive return periods, 2, 3, 5, 10, 25, 50, and 100 years, were estimated and compared. The return period for the highest recorded annual maximum daily water levels (4.4 m/day) in the Nokoue lake watershed were calculated to be 12, 15, and 15 years using the Gumbel, GEV, and GPA models, respectively. Quantile analysis revealed that the Gumbel distribution produced overestimated results compared to the GEV and GPA models for return periods exceeding 10 years. Exceptional and very exceptional hydrological events have return periods of 100 and 150 years, corresponding to peak flow levels of 4.95 m and 5.05 m respectively. Finally, the results of this study will be invaluable for flood hazard managers in monitoring flood alerts and for water resource engineers in determining dimensions for designing flood control structures such as spillways, dams, and bridges, thereby improving the management of recurrent flooding events. Full article

Modern product manufacturing is not only becoming more advanced but also requires increasingly precise and technologically advanced solutions, especially in the production process. One example is the automotive industry, where customization is becoming a key requirement. This work aimed to analyze the factors determining the efficiency of production processes, using the example of a selected company from the automotive industry—the production of spare parts—and to assess the impact of the applied optimization tools and techniques on improving operational results. This work combines theoretical and practical aspects, presenting a detailed analysis of data and actions taken in a real production environment. As part of the research, a thorough research program was presented, including the analysis of production data before and after conducting optimization workshops. Before the workshop, key problems were identified, such as the time-consuming rearranging of machines. The analysis using the parametric Student’s t test for two subsidiaries showed the rightness of the optimization activities. During the workshop, several changes were implemented, including the use of a new Destacker, modification of conversation procedures and training operators. The data collected after the workshop indicated a significant reduction in the times of reliance, which confirmed the effectiveness of the activities used. The analysis used tools such as the Pareto diagram and the ABC method, which allowed the identification of priority areas to improve. This work proves that the use of appropriate management tools and employee involvement in the optimization process can significantly improve the efficiency of production processes. Key success factors included the elimination of losses resulting from inefficient procedures, improvement of work organization and implementation of technological solutions. The results of this analysis form the basis for further research on improving production processes in the automotive industry. Full article

Gearboxes used in electric locomotives are a critical unit, especially in freight rolling stock. The article presents the calculation of the main parameters of the two-way oblique traction transmission of the VL-80s electric locomotive (which is operated on the railways of Uzbekistan) based on a comprehensive analysis of the diagnostic parameters obtained using the Poisson normal distribution method for the identified failures according to the Uzbekistan depot data. Also, a Pareto diagram was constructed for the chassis of 3VL-80s electric locomotives based on the data of the Locomotive Operation Department of JSC Uzbekistan Temir Yollari, and probabilistic and statistical analyses of the failures and breakdowns of the wheel pair and the large gear wheel of the traction gearbox of the VL-80s electric locomotives were carried out. An algorithm and methodology for assessing the reliability of the large gear wheel of the traction gearbox of an electric locomotive are presented. As a result of a numerical calculation of the coefficients of the empirical regression equations using approximation and spline interpolation methods, a regression equation was obtained for the dependence of the standard deviation of the wear of the tooth of the large gear wheel of the traction reducer of the VL80s electric locomotive on the mileage. Full article

With the development of algorithms for autonomous decision-making in the field of structural engineering, the design of precast concrete segment (PCS) box girder bridges faces new challenges. This paper proposes using a multi-objective optimization method based on genetic algorithms for the rapid design of PCS box girder bridges with small and medium spans. By considering 20 design parameters such as the physical dimensions of the box girder cross-section, material properties, and prestressing parameters, the paper formulates and quantifies three objective functions: cost, safety, and structural performance. The multi-objective optimization was conducted using four optimization algorithms (NSGA-II, NSGA-III, GDE3, and PSO). An optimization evaluation index ($\phi \left[F\right(x\left)\right]$) was established and weights were assigned to different optimization objectives. A specific design case based on the general diagram of a 3 × 25 m-long continuous PCS box girder bridge was carried out. The results indicate that genetic algorithms performed exceptionally well on this problem, with the NSGA-III algorithm achieving the best $\phi \left[F\right(x\left)\right]$ value of 0.2789 among all algorithms. A performance analysis was conducted on various optimization models using box plots and sensitivity studies. Scatter plots and surface plots of the Pareto front of the optimized solutions were generated, and corresponding cross-sectional design drawings were created based on the two proposed solutions. Compared with the general graph, the design cases provided by the NSGA-III algorithm model have a change rate of 8.03%, −0.29%, and 75.49% in the three optimization objectives, respectively, indicating a significant improvement effect. The research content of this paper provides a reasonable direction for future studies on intelligent bridge design methodologies. Full article

Background: Nanotechnology has been the main area of focus for research in different disciplines, such as medicine, engineering, and applied sciences. Therefore, enormous efforts have been made to insert the use of nanoparticles into the daily routines of different platforms due to their impressive performance and the huge potential they could offer. Among numerous types of nanomaterials, titanate nanotubes have been widely recognised as some of the most promising nanocarriers due to their outstanding profile and brilliant design. Their implementation in pharmaceutical applications is of huge interest nowadays as it could be of fundamental importance in the development of the pharmaceutical industry and therapeutic systems. Methods: In the present work, a risk assessment-based procedure was developed and completed using ANN-based modeling to enable the design and fabrication of titanate nanotube-based drug delivery systems with desired properties, based on the critical analysis and evaluation of data collected from published articles regarding titanate nanotube preparation using the hydrothermal treatment method. Results: This analysis is presented as an integrated pathway for titanate nanotube preparation and utilization in a proper way that meets the strict requirements of pharmaceutical systems (quality, safety, and efficacy). Furthermore, a reasonable estimation of the factors affecting titanate nanotube preparation and transformation from traditional uses to novel pharmaceutical ones was established with the aid of a quality by design approach and risk assessment tools, mainly an Ishikawa diagram, a risk estimation matrix, and Pareto analysis. Conclusions: To the best of our knowledge, this is the first article using the QbD approach to suggest a systematic method for the purpose of upgrading TNT use to the pharmaceutical domain. Full article

Reducing the flow rate (q) of the emitter can increase the dripline laying length and reduce the engineering investment of the drip irrigation system; however, reducing q increases the risk of emitter clogging. In this study, based on the OPFN method (Optimal Latin Hypercube Experimental Design–Parametric Modeling of Emitter–Fluid Dynamics Simulation–NSGA-II Genetic Algorithm Optimization), we selected the structural parameters of channel tooth height (E), angle (A), pitch of teeth (B), and flow channel depth (D) to construct 128 emitters. Through simulation, we obtained q, the flow index (x), and the structural resistance coefficient (Cs) under the pressure (H) ranging from 0.02 to 0.15 MPa. The results showed that the rated flow rate (q_0.1) and x values of 128 emitters range from 0.50 to 0.85 L/h and 0.461 to 0.480, respectively. Since Cs is negatively correlated with x, to obtain the combination of the flow channel structural parameters with the optimal hydraulic performance (x = min f(E, A, B, D)) and the optimal anti-clogging performance (Cs = min g(E, A, B, D)), the flow channel structural parameters are optimized by using the NSGA-II genetic algorithm to obtain the Pareto frontier solution. The optimal combinations of channel structural parameters corresponding to the q_0.1 values of 0.62, 0.71, and 0.82 L/h with x of 0.470, 0.466, and 0.463 are obtained using the weighting method. Cs values are 0.131, 0.446, and 0.619, respectively. The limit laying length of the configured emitter is 150–180 m. According to the flow field cloud diagram before and after optimization, it can be found that increasing the high-velocity area and high-turbulent-kinetic-energy area in the main stream and decreasing the low-velocity area and low-turbulent-kinetic-energy area in the tooth base and downstream face can help reduce x and Cs, and thus improve the hydraulic performance and anti-clogging performance of the small flow rate emitter. Full article

A Heating, Ventilation, and Air Conditioning (HVAC) system is often utilized in passenger vehicles to enhance the comfort of both the driver and the passengers. The reliability of an HVAC system refers to the probability that a component within the system will fulfil its intended function during a specified timeframe while operating according to the predefined operational and environmental conditions. Conducting a reliability analysis for the HVAC system of a passenger vehicle is crucial to ensure safety, comfort, cost-effectiveness, and a positive standing. A methodology for analyzing the reliability analysis of a HVAC system using field failure data were developed to identify the critical failure modes, components, and subsystems. A detailed Pareto analysis was applied at subsystem and failure mode levels in order to prioritize them accordingly to their failure frequency. The analysis showed that the A/C evaporator and blower front sides were observed to be the most critical subsystems, contributing to approximately 50% of all failures. Furthermore, the leakages at the joints and vibrations are the primary failure modes of the HVAC system. The Weibull++ software package (version 2021) was used to estimate the best-fit probability distributions for each subsystem and system reliability modelling using a Reliability Block Diagram. The results show that the exponential distribution fits well for several subsystem’s Time-To-Failure (TTF) data and show that the failures were random and due to external reasons. Full article

The paper presents a study related to the implementation of failure modes and effects analysis (FMEA). The analysis consists of the identification, assessment, monitoring, and control of potential failure modes specific to the injection process applied to veneer trim parts. Based on the Ishikawa diagram, potential failure modes, effects, and causes of failure can be determined. The assessment results show that the potential risks are mostly located in the medium and high zones. By implementing corrective action, the process is significantly improved, and the potential risks are located in the low and medium zones. From a qualitative point of view, the Pareto chart allows prioritization of the defects that appear for the analyzed manufacturing process. It can be noted that the first two types of identified defects represent 27% of the total defects. Full article

Potatoes are a crop that thrives in highland areas, and Bandung Regency is one of the major potato production centers in West Java. This production center is located in an environmentally focused village development area within the Cisangkuy Sub-Watershed of Bandung Regency. The purpose of this study is to identify risks arising from various risk sources and to formulate risk control strategies for potato production in this region. The method used is the house of risk (HOR) method. In farming activities, farmers must comply with environmental regulations. However, many farmers are still unaware of the importance of environmental sustainability, particularly in their use of chemicals. To actively engage in environmental management efforts, it is crucial to understand the characteristics of potato farmers in Bandung Regency, especially those located in the development area of environmentally focused villages within the Cisangkuy Sub-Watershed. The results of this study identified 33 risk events. The risk event with the highest impact is waterlogged plants (E10), with an impact value of 8.9. Based on the Pareto diagram, 16 priority risk sources need to be addressed. The most significant risk source identified is the use of uncertified seeds (A29). To mitigate risks in potato production, 21 preventive actions (PAs) have been proposed. One of the most effective strategies is for farmers to purchase seed potatoes directly from Balitsa (PA1), with an effectiveness ratio (ETD) of 4372. Another recommended strategy is to purchase certified seeds from other breeders (PA2). These strategies are prioritized to reduce the risks faced by potato farmers. Full article

Implementing quality tools and methods creates a basic foundation for innovations, sustainability, optimization, and competitiveness in the era of Industry 4.0 and Quality 4.0. This paper aimed to investigate the use of quality tools and methods in the 24 divisions of a mother manufacturing company without the influence of external factors such as geographical location (America, Africa, Asia, and Europe). It was important for the mother manufacturing company to implement a uniform process standard for innovation and performance. Research methods focused on using the Kanban card, Ishikawa diagram, affinity diagram, Flowchart, 5S, OPL, layout, and Pareto analysis. It was determined in this research that the synergy (combination) of quality tools and methods in divisions improves the process performance. This hypothesis was confirmed by the results of implementing quality tools in processes within divisions. A top result was the new innovative model of synergy of the quality tools and methods for divisions of the parent company thus filling a gap in the scientific field. This model created the basis for the uniform process standard in all divisions. The results brought improvements in the processes such as material input inspection, spare parts production, production process, and product packaging. This model could be a proactive instrument for process innovation. Full article

The evolution of aircraft wing development has seen significant progress since the early days of aviation, with static testing emerging as a crucial aspect for ensuring safety and reliability. This study focused specifically on the engineering phase of static testing for the Clean Sky 2 T-WING project, which is dedicated to testing the innovative composite wing of the Next-Generation Civil Tiltrotor Technology Demonstrator. During the design phase, critical load cases were identified through shear force/bending moment (SFBM) and failure mode analyses. To qualify the wing, an engineering team designed a dedicated test rig equipped with hydraulic jacks to mirror the SFBM diagrams. Adhering to specifications and geometric constraints due to several factors, the jacks aimed to minimize the errors (within 5%) in replicating the diagrams. An effective algorithm, spanning five phases, was employed to pinpoint the optimal configuration. This involved analyzing significant components, conducting least square linear optimizations, selecting solutions that met the directional constraints, analyzing the Pareto front solutions, and evaluating the external jack forces. The outcome was a test rig setup with a viable set of hydraulic jack forces, achieving precise SFBM replication on the wing with minimal jacks and overall applied forces. Full article

The optimal placement of healthcare facilities, including the placement of diagnostic test centers, plays a pivotal role in ensuring efficient and equitable access to healthcare services. However, the emergence of unique complexities in the context of a pandemic, exemplified by the COVID-19 crisis, has necessitated the development of customized solutions. This paper introduces a bi-objective integer linear programming model designed to achieve two key objectives: minimizing average travel time for individuals visiting testing centers and maximizing an equitable workload distribution among testing centers. This problem is NP-hard and we propose a customized local search algorithm based on the Voronoi diagram. Additionally, we employ an $ϵ$-constraint approach, which leverages the Gurobi solver. We rigorously examine the effectiveness of the model and the algorithms through numerical experiments and demonstrate their capability to identify Pareto-optimal solutions. We show that while the Gurobi performs efficiently in small-size instances, our proposed algorithm outperforms it in large-size instances of the problem. Full article