Cost Efficiency Research Articles

Extraction and Characterization of Silicon Dioxide from Coal Fly Ash as Counter Electrode Material in Dye-Sensitized Solar Cells (DSSCs)

The counter electrode in DSSCs must be made of a material with various advantageous chemical and physical characteristics to guarantee the cell’s efficient functioning and cost efficiency. Coal fly ash is recognized for its substantial silicon dioxide (SiO2) content and other minerals and metals. This paper provides a detailed analysis and description of extracting and characterizing SiO2 from coal fly ash. This extraction aims to utilize SiO2 as a material for the counter electrode in DSSCs. The extraction procedure of SiO2 from coal fly ash involves a multi-step process that entailed the utilization of acid leaching using hydrochloric acid 1 M at 90°C for 4 h, which was subsequently followed by precipitation using NaOH 3 M at 90°C for 4 h to separate SiO2. The SiO2 gel was cleaned of contaminants with hot distilled water and dried at 110°C for 12 h. The SiO2 that was obtained was analyzed utilizing a range of analytical techniques to evaluate its structural, morphological, chemical, and optical properties. The X-ray diffractometer (XRD) examination revealed that the crystal structure of coal fly ash consisted of quartz, corundum, hematite, lime, and periclase. The SiO2 that was obtained exhibited a crystal structure that was both cubic and triclinic. The morphology is visualized using a scanning electron microscope (SEM). The study using atomic absorption spectroscopy revealed that the coal fly ash contained 52.91% SiO2, whereas the extracted SiO2 had a purity of 91.20%. The UV-Vis spectrophotometry investigation revealed that the SiO2 exhibited absorbance spectra with a wide band gap of 4.17 eV, whereas the coal fly ash had absorbance spectra of 3.37 eV.

Crushing behavior and energy absorption of node self-locked Kagome honeycomb

This work proposes a self-locked Kagome honeycomb (SLKH) structure to realize better balance between energy absorption and cost efficiency. The structure uses a simple and creative bending preparation method to form a triangle nested self-locking pattern with distinct layers, rich shapes, easy assembly, flexibility and efficiency. The quasi-static experiments and numerical simulations are employed to investigate the energy absorption behavior and dynamic response. Numerical analysis is conducted to reveal the influence of cell size, angle at the connecting plate, and number of bent plates on the energy absorption performance of SLKH. Additionally, a theoretical estimation model for mean crushing force of SLKH structure is established, providing guidance for efficient parameter design and selection. The results demonstrate that the SLKH exhibits superior energy absorption performance with low cost.

Risk-informed design: An unavailability allocation approach

Due to the technological complexity of nuclear power plants and the large number of components involved in their design, the objective space for balancing nuclear safety, availability performance, and cost in an optimization model becomes extremely vast. Consequently, this poses challenges in achieving operational optimization at the plant level, complicating the assurance of compliance with regulatory requirements. One solution is to partition the problem and analyze it at a system level to reduce the objective space. In this work, different options are analyzed to optimize cost and unavailability for systems that provide the means for meeting previously proposed unavailability targets. This ensures that licensing basis events (LBE) comply with risk targets and regulatory criteria. Additionally, the role of system unavailability due to maintenance activities and reliability issues related to unplanned component failures (e.g., random failures, common cause failures) in the optimization problem is analyzed. The various proposed optimization methods are implemented in the design of a pressurized water reactor (PWR) system. Evolutionary algorithms are used as optimization methods, with Genetic Algorithms for single-objective problems and Non-dominated Sorting Genetic Algorithm III (NSGA-III) for multi-objective problems. The main finding suggests that traditional models, which aim to minimize costs and unavailability, face challenges in adapting to the systems unavailability target. Therefore, optimization occurs by shifting the focus towards minimizing costs and distance to the unavailability target. This approach ensures that the results closely align with the unavailability target, thereby creating more efficiency in operating and maintenance costs while also ensuring acceptable design and operational regulatory compliance.

Current developments and advancements of 3-dimensional printing in personalized medication and drug screening.

3-Dimensional printing (3DP) is an additive manufacturing (AM) technique that is expanding quickly because of its low cost and excellent efficiency. The 3D printing industry grew by 19.5 % in 2021 in spite of the COVID-19 epidemic, and by 2026, the worldwide market is expected to be valued up to 37.2 billion US dollars. Science Direct, Scopus, MEDLINE, EMBASE, PubMed, DOAJ, and other academic databases provide evidence of the increased interest in 3DP technology and innovative drug delivery approaches in recent times. In this review four main 3DP technologies that are appropriate for pharmaceutical applications: extrusion-based, powder-based, liquid-based, and sheet lamination-based systems are discussed. This study is focused on certain 3DP technologies that may be used to create dosage forms, pharmaceutical goods, and other items with broad regulatory acceptance and technological viability for use in commercial manufacturing. It also discusses pharmaceutical applications of 3DP in drug delivery and drug screening. The pharmaceutical sector has seen the prospect of 3D printing in risk assessment, medical personalisation, and the manufacture of complicated dose formulas at a reasonable cost. AM has great promise to revolutionise the manufacturing and use of medicines, especially in the field of personalized medicine. The need to understand more about the potential applications of 3DP in medical and pharmacological contexts has grown over time.

The bus selection based on PV curve for the photovoltaic integration into power grid

Thanks to cost reduction, efficiency improvement, and fast advancement in power electronics, renewable energy, particularly solar power is increasing exponentially in the global energy sector. On the one hand, the integration of solar energy into the electricity is subject to a number of technical and non-technical challenges. Technical challenges include uncertainty of output power, system stability, imbalance between supply and demand, lack of reactive power, harmonics, angular stability, etc. The non-technical challenges include environmental, social and economic issues. On the other hand, the voltage profile in the weak nodes of the system is improved by the integration of solar power. The main purpose of the work is to identify buses which are suitable for the solar plant integration in the Albanian Power System (APS) based on the Power – Voltage (PV) curve method. The APS is modelled as an 18-bus grid (220 kV and 400 kV). The system simulation has been performed in the software PSS/E. Based on the critical point values of the PV curves methodology, two buses are identified as the most suitable for solar plant integration in the applications.

Honeycomb ZIF-67 Membrane With Hierarchical Channels for High-Permeance Gas Separation.

Membrane technology exhibits low cost and high efficiency in gas separation. Zeolite-imidazole framework-67 (ZIF-67) membrane shows a theoretically superior performance in H2/CO2 separation, owing to its effective size-sieving pores between H2 and CO2. However, the gas molecules are permeate through a series of consecutive crystal cells of common ZIF-67 polycrystalline membranes, resulting in high transport resistance to the gas permselective transport. To this end, this work employs a contra-diffusion synthesis to construct a honeycomb ZIF-67 (h-ZIF67) crystalline membrane for low-resistance H2/CO2 permselective transport. The controlled growth of h-ZIF67 following the van der Drift theory produces the honeycomb polycrystal with hierarchical channels for low-resistance gas permeation. The prepared membrane with micron-scale thickness still achieves a H2 permeance as high as 1.6 × 10-7molm-2s-1Pa-1 and a H2/CO2 selectivity of 17, which can be maintained after a long-term operation for the H2/CO2 mixture separation.

Mathematical Modeling of the Global Engineering Process for Optimizing Product Quality in the Aerospace Industry

The aerospace industry faces the challenge of maintaining product excellence amidst intricate processes and demands for cost and time efficiency. Mathematical modeling emerges as a valuable tool for optimizing the engineering process and enhancing quality, with potential applications extending beyond aerospace to other sectors with high quality and safety standards. This study develops and validates a mathematical model specific to the aerospace industry, aiming to assess the impact of human resource expertise on product quality. Through a case study within an aerospace organization, an IDEF0-methodology-based mathematical model, coupled with weighted averages, was constructed to depict the comprehensive engineering process and quantify knowledge’s impact on deliverable quality. Simulation data, gathered through human resource knowledge assessments and non-conformity analyses, revealed a direct correlation between technical knowledge levels and deliverable quality, consequently impacting final product quality. The proposed model serves as a tool for estimating potential deliverable error rates and pinpointing critical areas within the process that necessitate refinement. The research underscores the significance of knowledge investment and effective knowledge management strategies in upholding quality and competitiveness across industries with stringent quality requirements.

The Design and Construction of Overcurrent Soft Starting on ESP32 Microcontroller Based Water Machine

The advancement of household water pump technology utilizing induction motors provides numerous benefits, such as efficiency and low cost, but also faces challenges like high inrush current. This study demonstrates the necessity of voltage reduction methods to address high inrush currents that can impact home electrical systems. Testing reveals that the device's error percentage is 0.31%, indicating good performance. The DHT22 and PZEM sensors operate optimally in detecting temperature and current, and controlling relays and water pumps according to the specified thresholds, achieving a 100% system success rate. These results confirm that the system operates as expected according to the specifications.

An automated phenotyping method for Chinese Cymbidium seedlings based on 3D point cloud

Aiming at the problems of low efficiency and high cost in determining the phenotypic parameters of Cymbidium seedlings by artificial approaches, this study proposed a fully automated measurement scheme for some phenotypic parameters based on point cloud. The key point or difficulty is to design a segmentation method for individual tillers according to the morphology-specific structure. After determining the branch points, two rounds of segmentation schemes were designed. The non-overlapping part of each tiller and the overlapping parts of each ramet are separated in the first round based on the edge point cloud-based segmentation, while in the second round, the overlapping part was sliced along the horizontal direction according to the weight ratio of the tillers above, to obtain the complete point cloud of all tillers. The core superiority of the algorithm is that the segmentation fits the tiller growth direction well, and the extracted skeleton points of tillers are close to the actual growth direction, significantly improving the prediction accuracy of the subsequent phenotypic parameters. Five phenotypic parameters, plant height, leaf number, leaf length, leaf width and leaf area, were automatically calculated. Through experiments, the accuracy of the five parameters reached 98.6%, 100%, 92.2%, 89.1%, and 82.3%, respectively, which reach the needs of various phenotypic applications.

Performance assessment and multi-objective optimization of a novel transcritical CO2 Rankine cycle for engine waste heat recovery

In this study, a novel self-condensing transcritical CO2 Rankine cycle, which integrates the three-stage expansion process with an ejector cycle, is proposed to recover engine waste heat deeply and overcome the condensation issue caused by the relatively low critical temperature of CO2. Thermodynamic and economic mathematical models are developed, and the detailed parametric analysis is carried out to investigate the effect of main parameters on both thermodynamic and economic performances of the system. Thereafter, a multi-objective optimization is conducted to trade off the two different performances. Results show that the proposed system could operate under higher temperature cold source conditions with desirable performance. The increases of turbine1 inlet pressure and LT gas heater outlet temperature, the decreases of LT gas heater outlet pressure and turbine3 back pressure are beneficial to achieve better thermodynamic and economic performances. On the basis of multi-objective optimization, the maximum net power output is 70.04 kW, which is a 10.20 % improvement compared to the reference cycle. Meanwhile, the engine power output could be increased by 7.03 % through adopting the novel system. Furthermore, the optimal exergy efficiency and unit net power cost are 37.02 % and 0.1567$/kWh, respectively.

In situ hydrolyzed microporous polymer membranes for additional free volume to facilitate CO2 permeation

Advancements in membrane separation technology play a pivotal role in separation processes closely associated with the environment and energy. However, presently available commercial polymeric membranes encounter the challenge of low permeability, impacting both separation efficiency and membrane module costs. Here, we propose a simple and effective in situ acid hydrolysis strategy to significantly enhance membrane permeability. Specifically, a tetrafluorinated monomer with hydrolyzable Schiff base groups (TFNAD) has been meticulously designed, synthesized, and copolymerized with commercial TFTPN and TTSBI, yielding a series of copolymers. Subsequently, in situ hydrolysis removes aniline from the membrane, freeing up the occupied free volume and creating additional channels for gas transport. This process substantially enhances gas permeability while preserving the desired selectivity. PIM-TFAD-30 showed a 68 % improvement in CO2 permeability with virtually no compromise in CO2/N2 selectivity compared to the pre-hydrolysis membrane. Meanwhile, PIM-TFAD-30 also displayed outstanding separation performance and plasticization resistance in simulated flue gas tests, demonstrating its potential for practical application. This facile and straightforward hydrolysis method opens up a new perspective for preparing and modifying polymeric separation membranes beyond gas separation.

Elimination of phenol by sonoelctrochemical process utilizing graphite, stainless steel, and titanium anodes: optimization by taguchi approach

Phenol is one of the worst-damaging organic pollutants, and it produces a variety of very poisonous organic intermediates, thus it is important to find efficient ways to eliminate it. One of the promising techniques is sonoelectrochemical processing. However, the type of electrodes, removal efficiency, and process cost are the biggest challenges. The main goal of the present study is to investigate the removal of phenol by a sonoelectrochemical process with different anodes, such as graphite, stainless steel, and titanium. The best anode performance was optimized by using the Taguchi approach with an L16 orthogonal array. the degradation of phenol sonoelectrochemically was investigated with three process parameters: current density (CD) (25, 50, 75, and 100 mA/cm2), time (1, 2, 3, 4 h), and phenol concentration (100, and 200 mg/l). Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were utilized to examine the impact of each factor. The optimal conditions for phenol removal were 100 mA/cm2, 100 mg/l of phenol, and 4 hours of electrolysis. Under optimal operating conditions, the phenol removal efficiency was 80.99%. The CD was the most influential factor on phenol elimination effectiveness, while the phenol concentration had the least impact.

COMPARISON OF VIRTUALIZATION TECHNOLOGIES TO OPTIMIZE THE USE OF HARDWARE IN DATA CENTERS

Virtualization is a key element in contemporary data centers, enabling efficient resource utilization, enhanced scalability, and cost reduction. This study aims to enhance the comprehension of virtualization technologies and guide the deployment of effective virtualization strategies in data centers. It conducts an analysis of hypervisors such as Hyper-V and Oracle VM VirtualBox, focusing on comparing their physical processor load. This comparison highlights the strengths and weaknesses of each hypervisor, providing insights into their optimal use cases and aiding in informed decision-making for data center optimization. The analysis reveals that Hyper-V offers superior performance and resource allocation efficiency compared to Oracle VM VirtualBox. This superiority is due to Hyper-V's optimization for enterprise and cloud environments, which require high levels of security, reliability, and scalability. Consequently, for data centers aiming for optimal resource utilization Hyper-V is the preferred choice. While Oracle VM VirtualBox demonstrates efficacy in smaller-scale projects and testing scenarios, Hyper-V offers enhanced capabilities tailored for scalable and mission-critical workloads.

Use of Building Information Modeling (BIM) to Improve Construction Management in the USA

The construction industry in the United States faces ongoing challenges related to cost overruns, project delays, and inefficiencies in project management. Building Information Modeling (BIM) has emerged as a transformative technology with the potential to address these issues by enhancing the precision, collaboration, and decision-making processes in construction management. This paper provides a comprehensive review of the application of BIM in the U.S. construction sector, with a focus on its impact on improving construction management practices. The review explores the specific ways in which BIM contributes to project success, including its ability to streamline workflows, reduce errors, and facilitate real-time collaboration among stakeholders. Through an in-depth analysis of current literature, this paper highlights the specialized functions of BIM that are particularly beneficial for construction management in the U.S., such as clash detection, 4D scheduling, and cost estimation. The paper also examines case studies that demonstrate the successful integration of BIM in large-scale projects across the country, showcasing tangible improvements in project outcomes, including reduced project timelines and enhanced cost efficiency. Additionally, the paper delves into the challenges associated with BIM adoption in the U.S., including the need for skilled personnel, the integration of BIM with existing project management systems, and the legal and contractual implications of BIM-based collaboration. These challenges are discussed alongside strategies for overcoming them, emphasizing the importance of training, standardization, and cross-disciplinary collaboration. The findings of this review suggest that the widespread adoption of BIM in the U.S. construction industry holds significant promise for enhancing project management efficiency, improving stakeholder communication, and ultimately contributing to more successful project outcomes. The paper concludes by proposing best practices for BIM implementation in construction management, aiming to guide industry professionals in leveraging this technology to its fullest potential.

Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 1.0.0.1) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

DESIGNING A MICROSERVICES BASED ENTERPRISE ARCHITECTURE USING TOGAF 10: A CASE STUDY APPROACH

PT Umbara Karya Sejati, operating in the home living and industrial product sectors, faced significant digital transformation challenges, marked by inefficiencies due to system integration issues and vendor dependencies that incurred cost penalties of 10-15% each month. Addressing these challenges, this research developed an Enterprise Architecture using TOGAF 10's Microservices Architecture (MSA) from the Preliminary Phase to Phase F: Migration Planning. This approach aimed to enhance system integration and operational efficiency, thereby improving modularity and scalability while reducing reliance on external vendors. A pivotal component of this architecture, an API gateway, provided robust monitoring capabilities for integration processes, enabling quick identification and prioritization of critical issues, which will assist the internal IT team's workflow. Furthermore, the research planned the establishment of a DevOps team, incorporating Agile methodologies, and scheduled IT governance and data security training to prepare for future policy development and strengthen internal controls. This strategic design equips the organization to navigate the volatility, uncertainty, complexity, and ambiguity (VUCA) of market demands with agile and effective responses, projecting a 10% increase in both operational and cost efficiency for PT Umbara Karya Sejati.

The Role of Virtualization Technology to Increase Operational Cost Efficiency of Indonesian SMEs: Case Study of Internet Service Providers

This research investigates the role of virtualization technology in enhancing operational cost efficiency for Indonesian Small and Medium-sized Enterprises (SMEs), specifically Internet Service Providers (ISPs). A quantitative approach, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) version 2.0, was employed to analyze data collected from 68 respondents representing 216 Indonesian SME ISPs. The study focused on the relationship between virtualization technology planning, adaptation capability, server consolidation services, and operational cost effectiveness. The findings demonstrate that adaptability to virtualization technology is the most significant factor influencing operational cost efficiency. Effective implementation requires careful planning and a proactive approach to adapting to the technology's demands. Server consolidation services play a crucial role in optimizing resource utilization and reducing costs while virtualization technology offers substantial benefits, SMEs should carefully assess their specific needs and resources before implementation. Factors such as infrastructure, skills, and business objectives should be evaluated to ensure successful adoption and maximize cost savings. This research provides a foundation for further exploration into the impact of virtualization technology on SMEs. Future studies could investigate the applicability of these findings in different contexts, such as other industry sectors or regions. Additionally, examining the long-term effects of virtualization technology adoption and the potential for scalability could offer valuable insights. Further research could also focus on the challenges and opportunities associated with virtualization technology adoption in SMEs with varying sizes and resources.

An Eco-Driving Strategy at Multiple Fixed-Time Signalized Intersections Considering Traffic Flow Effects

To encourage energy saving and emission reduction and improve traffic efficiency in the multiple signalized intersections area, an eco-driving strategy for connected and automated vehicles (CAVs) considering the effects of traffic flow is proposed for the mixed traffic environment. Firstly, the formation and dissipation process of signalized intersection queues are analyzed based on traffic wave theory, and a traffic flow situation estimation model is constructed, which can estimate intersection queue length and rear obstructed fleet length. Secondly, a feasible speed set calculation method for multiple signalized intersections is proposed to enable vehicles to pass through intersections without stopping and obstructing the following vehicles, adopting a trigonometric profile to generate smooth speed trajectory to ensure good riding comfort, and the speed trajectory is optimized with comprehensive consideration of fuel consumption, emissions, and traffic efficiency costs. Finally, the effectiveness of the strategy is verified. The results show that traffic performance and fuel consumption benefits increase as the penetration rate of CAVs increases. When all vehicles on the road are CAVs, the proposed strategy can increase the average speed by 9.5%, reduce the number of stops by 78.2%, reduce the stopped delay by 82.0%, and reduce the fuel consumption, NOx, and HC emissions by 20.4%, 39.4%, and 46.6%, respectively.

Mechano‐Electrochemical Behavior of Nanostructured Li‐ and Mn‐Rich Layered Oxides with Superior Capacity Retention and Voltage Decay for Sulfide‐Based All‐Solid‐State Batteries

AbstractLi‐ and Mn‐rich layered oxides (LMROs) are recognized as promising cathode materials for lithium‐ion batteries (LIBs) due to their high specific capacity and cost efficiency. However, LMROs encounter challenges such as manganese dissolution in electrolytes and the release of oxygen gas from irreversible oxygen redox reactions, leading to structural degradation and voltage decay that reduce energy density. Consequently, recent research has shifted toward employing LMROs in all‐solid‐state batteries (ASSBs), where Mn dissolution is negligible. Herein, nanostructured LMROs demonstrate superior electrochemical compatibility with sulfide‐based solid electrolytes in ASSBs compared to conventional LIBs. Nanostructured LMRO exhibits outstanding capacity retention (97.1% after 1300 cycles at 30 °C) with significantly suppressed voltage decay. Furthermore, the initial electrochemical activation of Li2MnO3 domains within LMRO is explored in terms of the mechano‐electrochemical interactions in the composite cathode. At elevated temperatures, interfacial degradation accelerates due to the chemical oxidation of Li6PS5Cl solid electrolytes, driven by oxygen released from LMRO. To address this, LMRO surfaces are modified with thioglycolic acid through esterification, suppressing interfacial degradation of Li6PS5Cl and ensuring stable capacity retention over 500 cycles at 60 °C. These findings underscore the potential of LMRO materials as promising cathode options for ASSBs, surpassing those used in LIBs.

ECONOMIC EFFICIENCY OF GROUNDNUT PRODUCTION IN KANO STATE, NIGERIA

The study examined the economic efficiency of groundnut production in Kano State, Nigeria. Using a simple random sampling, two hundred and sixty-seven (267) farmers were selected and interviewed from nine communities, under the three selected LGAs from the study area. Descriptive statistics, DEA, as well as Tobit regression model were used for data analysis. The result of the Data Envelopment Analysis (DEA) reveals that the farmers were operating below the optimum frontier with average Technical Efficient (TE), Allocative Efficiency (AE) and Economic Efficiency (EE) scores was 0.265, 0.371 and 0.098 respectively, with the GM enterprise having a higher mean TE score of (0.7654). All the inefficiency variables met a prior expectation with positive coefficients except age and level of education. This indicates that increase in age and years of schooling have minimal effect in reducing the farmers’ inefficiency in groundnut production. Four out of the eight fitted inefficiency variables were significant at 10%, while three at 5%, but the extension contact was not significant. It was thus concluded that even though groundnut production enterprise is a profitable one, groundnut farmers in the study area were both technical and allocative inefficient. It was therefore recommended that farmers should be encouraged through extension to adopt new available technologies and improved varieties which will help improve both their technical and cost efficiency thereby widen their margin gaps.