Evaluating the Sustainability of Metro and Feeder Bus Integration: A Bengaluru Metro Case Study in India

Rapid urbanization and an increase in private vehicle ownership in India's major cities have contributed to increased traffic congestion, pollution, and accidents. These challenges could be addressed in part by encouraging commuters to use public transport instead of private vehicles. The integration of different transport systems would be essential for increasing the utilization and efficiency of public transportation. It is essential to evaluate the existing level of integration among various transport systems to improve it. Consequently, the objective of this research is to adapt a methodology for evaluating the existing level of integration between metro and feeder buses while keeping sustainability as a goal. For evaluation, 18 sustainable transportation indicators were considered. To estimate the Sustainability Integration Index (SII) value, data were collected from transport hubs and nearby bus stops in Bengaluru, India. The multi-criteria method was used for the homogenization of transportation indicators. Based on the expert opinion survey, additional appropriate weights were obtained for each indicator, and the final SII value for selected metro stations was estimated in the range of 0 to 100. The adapted methodology was used to evaluate three transport policies in Bengaluru city relating to the integration of metro and feeder bus services. According to the analysis, the policy of increase in bus frequencies had the highest SII value, with an average increase of 4.97%, followed by policies of relocating bus stops and single ticketing systems, which had average increases of 3.49% and 4.58%, respectively

Numerical Investigation of Enhanced Efficiency in CIGS Solar Cells with 3C-SiC and PEDOT:PSS Integration

Copper indium gallium selenide (CIGS)-based thin-film solar cells continue to lead advancements in the efficiency of thin-film technologies. In this study, we propose cubic silicon carbide (3C-SiC) as a viable alternative to cadmium sulfide (CdS) for use as a buffer layer in CIGS solar cells. 3C-SiC offers superior transparency, higher electron mobility, and non-toxicity, making it a promising candidate for enhancing device efficiency. In this paper, we present a computational analysis of a thin-film solar cell utilizing a ZnO/3C-SiC/CIGS/ poly(3,4-ethylenedioxythiophene) (PEDOT): polystyrene sulfonate (PSS)/Mo heterostructure with PEDOT:PSS as the back surface field (BSF) layer. Simulations conducted using SCAPS-1D software demonstrate impressive photoconversion efficiencies, achieving an ideal efficiency (η) of 32.83%, an open circuit voltage (VOC) of 0.86 V, a short circuit current density (JSC) of 56.40 mA cm−2, and a fill factor (FF) of 80.79%. The study systematically examines the influence of key parameters, including CIGS absorber thickness, PEDOT:PSS thickness, 3C-SiC thickness, and temperature, demonstrating a strong correlation with previous experimental results. These findings offer valuable insights for enhancing the performance of CIGS solar cells and highlight promising avenues for future advancements in thin-film photovoltaics

Investigation of the Effects of Rock Components for Different Pyroclastic Rocks on Leeb Hardness

The aim of this study is to research the effect of rock components on Leeb hardness (HL), a non-destructive test commonly used in recent periods. With this aim, cube samples of two different pyroclastic rocks containing dominantly pumice (P) or volcanic rock fragments (VRF) were prepared. Later, the proportions of different components (P and VRF) on the surfaces of the cube samples were determined using the Image Pro Plus 6.0 image processing program. The effect of the variation in these components on HL values was researched with simple regression analysis and strong correlation coefficients were found between these values. According to the data obtained, the HL test was identified not to be suitable for heterogeneous rocks comprising different components

Chaos-based Swarm Intelligence Algorithms for Optimal Design of Truss Structures

The incorporation of chaos functions into metaheuristic algorithms leads to significant progress in the results of optimal design of truss structures. Chaos functions, by forming chaotic mutations, create the necessary conditions to create a balance between exploration and exploitation. With this balance, the algorithm is saved from premature convergence and, by forming chaotic series, a jump from local optima to global optima is achieved. In this research, chaos functions are formed in the basic steps of three meta-heuristic swarm intelligence algorithms and three new chaos algorithms. These algorithms include the Chaotic Grey Wolf Optimizer (CGWO), the Chaotic Crow Search Algorithm (CCSA), and the Chaotic Cyclical Parthenogenesis Algorithm (CCPA). To improve the optimization results, three different scenarios are examined and the chaotic results are compared with the standard case. In these scenarios, chaos series replace the exploration, exploitation, or both stages simultaneously

Hydrothermal Synthesis and Photocatalytic Efficiency of Turmeric Leaves Biochar/TiO2 Composite for Photooxidation of Congo Red Dye

The hydrothermal synthesis of an eco-friendly photocatalyst using turmeric leaves biochar (TLB) and titanium dioxide nanoparticle composite has been reported for the degradation of Congo Red (CR) dye. The synthesized composite was characterized using various analytical techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) analysis, Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS), confirming its structural and morphological attributes that ensured the uniform dispersion and intimate contact between TLB and TiO2 particles. The degradation performance of the TLB/TiO2 composite was examined by using UV light irradiation as a catalyst. The results demonstrated that the TLB/TiO2 composite exhibited superior photocatalytic activity compared to pristine TiO2, attributed to the enhanced light absorption, improved charge separation, and increased surface area provided by the biochar. The degradation kinetics followed a pseudo-first-order model, with a significant reduction in the dye concentration within a short time frame. The eco-friendly nature, cost-effectiveness, and high photocatalytic efficiency of the TLB/TiO2 composite highlight its potential application in wastewater treatment, thus providing a novel approach to valorize agricultural waste into functional materials for sustainable environmental technologies

Adsorption of Phenol Using Activated Carbon Derived from Polystyrene, Paper and Wood Mixtures

The removal of phenol from wastewater is essential due to its toxicity, persistence, and environmental risks. Among various treatment methods, activated carbon (AC) adsorption is widely preferred for its efficiency and cost-effectiveness. This study examines the production of AC from polystyrene (PS), paper, and wood ‒ common components of refuse-derived fuel (RDF) ‒ and evaluates their phenol adsorption capacity. The aim was to assess potential interactions during thermal treatment and their impact on adsorption performance. The results showed that for most mixtures, co-carbonization reduced adsorption capacity compared to separately activated components, indicating negative thermal interactions. However, a positive adsorption-related synergy was observed for the PS/wood mixture. BET surface area analysis revealed that paper-containing mixtures exhibited significantly lower surface areas than expected, likely due to the inhibition of gasification reactions, resulting in reduced adsorption performance. This study highlights how RDF components influence AC properties and provides insights for optimizing waste-derived adsorbents in wastewater treatment

Mathematical Remodeling: Hierarchical Sensitivity Analysis Approach Based on Analysis of Finite Fluctuations

To make the process of evaluating complicated hierarchical systems more tractable, it is beneficial to represent them through models derived from a unified class of frameworks that are conducive to subsequent analytical endeavors. This method of interchanging the original model with ones from predetermined categories possessing desirable characteristics is referred to as Mathematical Remodeling. Among remodeling classes there can be mentioned Neural Networks as structures being universal approximators and which are acceptable to be analyzed. The question related to the importance of model inputs (Sensitivity Analysis) has a great practical meaning, for example, this information can be used for model reduction, control of the system, etc. There are a wide variety of methods of Sensitivity Analysis, which can be classified both by the mathematical approaches used and by the types of models to which they are relevant. However, there are almost no unified approaches to assessing sensitivity in the case of hierarchical systems. The paper introduces the approach to estimate sensitivity measures for hierarchical system obtained by applying remodeling concept. The proposed method is based on Analysis of Finite Fluctuations built on the Lagrange mean value theorem. The proposed approach provides both end-to-end analysis (investigation of the influence of inputs of sub-systems on the output of the main system) and analysis of the components of the hierarchical system. The paper also contains a numerical example which demonstrates the ability of the proposed approach to deliver sensitivity measures of hierarchical system

Sensitivity Parameters of Transport Networks and Vulnerability Assessment of Critical Network Elements: Literature Review

Network sensitivity has recently become an important topic, with an increasing number of articles appearing on the subject. Identification of critical sections within transport networks is also essential for transport modelling. A well-developed methodology can help to improve the network to minimize the impact on road users in the event of future emergency cases (accidents or attacks). For this purpose, existing articles were assessed to determine what progress has been made in network sensitivity and what parameters and approaches have been used so far. After reviewing the articles, it became clear that a significant number of methods have been used to identify critical sections, and it became visible which areas are worth further work. Among the methodologies used, simplified networks have been the main focus, but there is a need for a more detailed analysis based on industry demand and available data