Economical Solution Research Articles

Modified evacuated tube collector basin solar still for optimal desalination of reverse osmosis concentrate

This study focused on the optimal production feasibility of distilled water from the concentrate of a reverse osmosis device using an evacuated tube collector basin solar still. The characteristic effect of the device's condenser on the produced freshwater volume was evaluated to improve the performance of the solar still, resulting in productivity enhancement. The direct contact of two faces of the cubic condenser with water vapor results in the doubling of the effective surface area. However, freshwater production was decreased by eight times compared to the case where only one face of the condenser is in contact with water vapor. This reduction was attributed to the shorter path taken by the condensed droplets. At the bottom of the evacuated tube collector, some building mineral pumice was used to prevent the formation of large water vapor bubbles. According to this methodology, the average daily production of distilled water from the concentrate of the reverse osmosis unit with a total dissolved solids of 15200 ppm was achieved at 4.58±0.12L.m−2. The quality of produced distilled water revealed that solar desalination using an evacuated tube collector basin solar still can be a notable and economical solution for the concentrate treatment of reverse osmosis.

Research on Static and Dynamic Loading Performance of Geosynthetic Reinforced and Pile-Supported Embankment

Geosynthetic reinforced and pile-supported (GRPS) provide an economic and effective solution for embankments. To investigate the load-bearing mechanism of the GRPS embankment in loess, experimental and numerical studies under static and dynamic loading are carried out. The characteristics of soil arch effect and tensile membrane effect of GPRS embankment under static and dynamic loading are revealed by analyzing pile–soil stress ratio, tension of geogrid, and stress distribution of pile. The test results show that the pile–soil stress ratio under dynamic loading is reduced by 2.3 compared with static loading. In comparison to static load, the soil arching effect is attenuated under dynamic load, and the stronger the static load soil arching effect, the greater the degree of weakening under dynamic load. In addition, under dynamic loading, the tensioned membrane effect is still effective, but its enhancement is not as pronounced as under static loading. Furthermore, by using the finite element software, the numerical model is developed and validated with the experimental results. The parameter analysis of the load-bearing performance of the GRPS embankment is accomplished using the finite element model as well.

Regulation engineering of lignin-derived N-doped carbon-supported FeNi alloy particles towards efficient electrocatalytic oxygen evolution

The electrocatalytic hydrogen production technology using green energy can reduce the dependence on traditional fossil fuels and the net emission of carbon dioxide. However, the high overpotential and low efficiency of the oxygen evolution reaction (OER) on the anode limit the overall water splitting. Here, carboxylic acid ligands with coordination function were designed and synthesized by modifying the surface functional groups of lignin. Bimetallic functionally-doped lignin-derived carbon materials (Fe4Ni4@NC) were synthesized by continuous ion layer adsorption and pyrolysis process using Fe and Ni transition metals as source and template. The catalyst requires only 214 mV of overpotential to produce 10 mA·cm−2, which has much faster catalytic kinetics. Theoretical calculation shows that the energy barrier of rate-determining step in OER is reduced by appropriate feed ratio and nano-size. The facile strategy opens up an economical and efficient solution for designing OER electrocatalysts with high catalytic activity and excellent stability.

Off-the-shelf optical systems design enabled by an evolution strategy: front stop case

Commercial off-the-shelf optics enable economic and rapid solutions in the photonics industry and academia. However, the design of optical systems with off-the-shelf optics is a time-consuming task for experienced optical designers and hopeless for novice designers. In this paper, we propose an automatic optical design tool to generate optical systems using only off-the-shelf optical components without human assistance. Our solution is based on an evolution strategy (ES) that performs a discrete combinatorial optimization following optical design-based methodologies that satisfy user-defined specifications. Unlike the conventional methods, the algorithm decreases the design process time and provides optical designers with several optical solutions from where to choose and adapt for targeted applications. In this work, the ES is described and tested with front stop optical configurations. We demonstrate the broad solution domain of the algorithm through the generation of optical systems with F-numbers within a range F/1 to F/90 and field of views up to 300 mm at the image plane. To analyze the solution domain and the characteristics of the solution, we used the design specifications of 29 commercially available scan lenses and compared the performance of different ES parameters. The compatibility of our algorithm with (standard) commercially available optical design software unlocks automatic design tools for off-the-shelf optical systems.

Reactive nitrogen fluxes from soils to atmosphere in baby corn based cropping system

A field study with varying nitrogen (N) rates (0–150 kg N ha−1) was conducted in Ludhiana (Punjab, India) in a randomized complete block design in three consecutive baby corn seasons to quantify and mitigate N losses to the environment. The nitrous oxide (N2O) flux emissions were measured at 2, 4, 8, 16, and 24 days after each fertilizer N split application. The leachate N losses were estimated by analyzing ammonium and nitrate ion content. Fertilizer N surplus to crop requirement explained 94.1% (spring), 95.9% (summer), and 95.5% (winter) variation in the area-scaled N losses (N2O + leachate). Lower fertilizer N usage by plants at early growth stages (upto V6 stage) resulted in higher N losses within ten days after the first fertilizer application. Carbon equivalent emissions followed the trend summer > spring > winter. Temporal variations during the monitoring seasons influenced the cob and stover yield in response to fertilizer N. On average, 67.9% of the applied fertilizer N was taken up by plants, 4.7% was lost via N leaching, 2.7% escaped as N2O, 3.2% accumulated in the soil profile, and 21.5% remained unaccounted. Sensing-based N application significantly improved N recovery efficiency by 51.2%, mitigated N emissions by 45.4%, and N leaching by 69.3% in comparison with fixed-time blanket fertilizer N topdressings. Fertilizer N management using PAU-LCC provided an economical and farmer-friendly solution to achieve a significant reduction in N losses while sustaining productivity. Further validation and transfer of technology to on-farm locations are needed to benefit from this work.

Design and Simulation of Hybrid Shunt Active Filter for PQ Improvement using PID Genetic Algorithm Controller in 3ϕ-4 Wire System

This paper provides an economical solution and advanced method by tuning and optimizing system for power in the transmission line. The proposed system uses PID Genetic Algorithm (GA) controller in three phase four wire system for Total Harmonic Distortion (THD) minimization under balanced load conditions. In this article, traction load model is taken into consideration to evaluate the designed Shunt Active Power Filter (SAPF) for reduction of harmonics in three phase four wire system. Many existing SAPF models were tested using non-linear diode rectifier load for analysis. The GA technique for the reduction of harmonics is used to tune PID parameters such as a proportional (Kp), Integrator (Ki), and Derivative (Kd). In contrast with other controllers such as PI Controller, Fuzzy Logic Controller (FLC), Hysteresis Controller (HC), Sliding Mode Controller (SMC) and Synchronous Reference Frame Theory (SRFT), the performance of the proposed controller is compared. The performance of the designed controller with GA adjusted PID is validated at various loading conditions by comparing it to the performance of the existing system. The outcomes are addressed to demonstrate the effectiveness of the created system.

Exploring the Product of Campus Service-based Sharing Economy - A Case Study of Shared Laundry Services at Jiangsu University of Science and Technology

As an emerging economic model, sharing economy has been widely used and promoted on campus, such as library book sharing, database resource sharing, MOOC platform, shared bicycles and shared laundry. The campus service-based sharing economy aims to enhance efficiency and convenience within the campus by sharing resources and services. Taking the shared laundry service of Jiangsu University of Science and Technology as an example, this paper discusses the product of campus service-based sharing economy, and analyzes its impact on campus environment and student life. The study found that shared laundry services reduce the burden on students' lives and promote the efficient use of campus resources by providing convenient and economical laundry solutions. However, the service also has some shortcomings in the implementation process, such as equipment problems and health problems. In view of these problems, this paper puts forward some solutions and looks forward to the development of a campus service-oriented sharing economy in the future.

An Auto-Detection and classification algorithm for identification of sand dunes based on remote sensing images

Dunes are among the most abundant aeolian landforms found on Earth and other planets. The automatic mapping of dunes over large-scale areas is crucial for predicting, monitoring, and managing lands threatened by sand encroachment. However, the spectral similarity between dune and inter-dune areas, as well as the diverse presentations of dunes of the same type, have made it challenging to automatically classify and map dunes. In this study, we propose a two-step 'detect-then-classify' framework that enables the automatic identification of heterogeneous dune types. The first step involves dune detection. We introduce a newly developed convolutional neural network called SandUnet, which is adapted from Attention U-Net. This network is designed to preserve uncompressed input signals ensuring that minor differences in the color and texture of the dunes are retained. The second step focuses on dune-type classification. To classify dunes, a fine-tuned MobileNet was constructed to integrate the wealth of knowledge ingrained in MobileNet's pre-trained layers with the adaptations tailored specifically for the sand dune images. Subsequently, each dune image is automatically classified into six different types using this framework. By applying this framework to all the bare sand areas of the Taklamakan (or Taklimakan) Desert using Landsat-8 imagery, the final classification of dune types of the desert was achieved. Testing on randomly selected 10% image patches of whole desert, the overall accuracy of the dune-type classification is 70%. This study presents an automatic and economical solution for identifying dunes in large-scale areas.

The Impact of National Financing Initiatives on SMEs: An Applied Study

The relationship between financing programs and national initiatives and small projects has been studied, and it has been shown that there is a strong relationship between them, These programs and initiatives aim to enable the people, especially young people and women, to implement small projects that contribute to providing job opportunities, income, and vocational education, and to provide economic solutions and new ideas that contribute to the growth of the overall economy, as well as handicrafts and crafts. They contribute to enhancing financial freedom and the ability to control family economic decisions and change the income map in the neediest areas. The study emphasizes the importance of providing scientific, technical, and material support to project owners and workers, providing training and simulation opportunities, and transferring expertise. The study also indicates that investment incentives contribute to the stability of small projects and improve their ability to compete, and directly affect the ability of small projects to exist and survive in difficult economic conditions. In addition, the study found that the support provided by comprehensive and integrated support, consulting and training services is essential for the success of small projects, as most of these projects depend on skills that require training, simulation and transfer of expertise. The study also showed the importance of investment incentives in creating a strong impact on the stability of small projects and the surrounding community. Therefore, it can be said that integrated and comprehensive support is a key factor for the success of small projects and the achievement of the desired economic and social goals. Keywords: Funding initiatives – Small and medium enterprises – The Egyptian environment

The Impact of National Financing Initiatives on SMEs: An Applied Study

The relationship between financing programs and national initiatives and small projects has been studied, and it has been shown that there is a strong relationship between them, These programs and initiatives aim to enable the people, especially young people and women, to implement small projects that contribute to providing job opportunities, income, and vocational education, and to provide economic solutions and new ideas that contribute to the growth of the overall economy, as well as handicrafts and crafts. They contribute to enhancing financial freedom and the ability to control family economic decisions and change the income map in the neediest areas. The study emphasizes the importance of providing scientific, technical, and material support to project owners and workers, providing training and simulation opportunities, and transferring expertise. The study also indicates that investment incentives contribute to the stability of small projects and improve their ability to compete, and directly affect the ability of small projects to exist and survive in difficult economic conditions. In addition, the study found that the support provided by comprehensive and integrated support, consulting and training services is essential for the success of small projects, as most of these projects depend on skills that require training, simulation and transfer of expertise. The study also showed the importance of investment incentives in creating a strong impact on the stability of small projects and the surrounding community. Therefore, it can be said that integrated and comprehensive support is a key factor for the success of small projects and the achievement of the desired economic and social goals. Keywords: Funding initiatives – Small and medium enterprises – The Egyptian environment

Attraktive Finanzbildung für junge Menschen mit CashCoach

Abstract Financial education can sustainably improve the financial behaviour of young adults, empower them in their decisions and help them recognise opportunities and risks. Digital tools linking financial content with innovative learning methods have an outstanding potential to be an attractive offer for younger individuals. An app that includes interactive game elements was developed by students from St. Michael Schwäbisch Hall high school for the YES! – Young Economic Solutions student competition and won the “Best Scientific Analysis Award”.

Aerodynamic Improvements of Buses Inspired by Beluga Whales

The innovative bus designs, inspired by the whales, have been developed. The designs are confined to the frontal area of the buses. The new designs are named as the Beluga buses. Several variants of the models all mimicking Beluga whales are proposed. Both numerical analysis and experimental have been conducted to determine the drag coefficients of various models. The ANSYS CFD program was used for numerical simulations. WT tests were conducted to experimentally determine the drag coefficients. Both methods indicate that the beluga-inspired buses offer significant reductions in drag, which can lead to lower fuel consumption. The new beluga design is expected to reduce fuel consumption by 12.64%. Comparing the experimental and numerical results, a 6.4% discrepancy in the drag coefficients is observed at low Reynolds numbers, which became negligible at higher Reynolds numbers. The new geometry is expected to offer an economical solution for reducing fuel consumption.

Increasing cerium dispersion favours lattice oxygen activity of cobalt oxides for CO catalytic combustion

Removing carbon monoxide with catalytic combustion technology is an effective and economical solution. Highly efficient conversion of CO at low temperatures can be achieved by introducing a catalyst, and its application in automotive exhaust emissions and preferential oxidation of CO in fuel cells is remarkable. In this work, catalysts were prepared by mixing the prepared cerium organic framework with Co3O4, and after calcination at 400 °C, the organic framework collapsed, resulting in a uniform dispersion of Ce on the Co3O4 nano surface. Experimental results demonstrated that the required temperature of the catalyst is 101 °C when the conversion is 90 %, and it remained stable over the 75 h tested at 100 °C. High resolution transmission electron microscopy (HRTEM) revealed that Ce/Co3O4 primarily exposed 311 surface. Combined with DFT calculations, the catalysts may improve the catalytic combustion activity of CO by multiplying the oxygen vacancies and modulating the dispersion of Ce atoms. The reaction occurred on the 311 surface predominantly. Activated CO* preferred to react with the lattice oxygen at the Ce-O-Co linkage compared to the lattice oxygen at Co-O-Co. Energy barrier for the rate dictating step in the complete catalytic cycle is 0.42 eV. This work not only provides experimental support and theoretical basis for the design of low-temperature catalytic combustion CO catalysts, but also provides new ideas for the doping of metal oxides with lanthanide metals.

Boosting bacterial nanocellulose production from chemically recycled post-consumer polyethylene terephthalate

The circular economy is emerging with new sustainable solutions to the ever-growing plastic waste challenge, garnering increasing attention. In this study, the possibility to modify expensive Hestrin–Schramm medium (HS) for bacterial nanocellulose (BNC) production and replace significant amounts of glucose with terephthalic acid (TPA) derived after reactive extrusion processing of mixed plastic waste yielding post consumer TPA (pcTPA), was evaluated from laboratory scale to fermentation at pilot scale. Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), Thermogravimetric Analysis (TGA) were used to assess the structural, thermal, and morphological properties of BNC and its generated derivatives. The study's findings highlight the positive impact of pcTPA on BNC yield, surpassing the performance of conventional TPA. The presence of pcTPA in the medium resulted in a BNC yield of 4.01 g/L in a scale-up step of 100 mL cultivation, while the positive control using glucose resulted in a yield of 3.57 g/L. The efficiency of glucose substitution with pcTPA increased with each scale-up step, ultimately reaching a 320% yield increase in comparison to the positive control. Additionaly, the procedure that enhanced the materials' thermoplasticity in the form of derivatives has been established resulting in the production of BNC laurate and BNC octanoate derivatives with melting temperatures of 270 °C and 280 °C, respectively. Overall, this study investigates the potential of this approach as an important circular economic solution, enabling an increased sustainable perspective for polyethylene terephthalate (PET) circularity and significantly a much needed cost reduction for BNC production with enhanced thermoplasticity.

Real-time yaw-misalignment calibration and field-test verification of wind turbine via machine learning methods

It has become a general consensus that nacelle-mounted LiDAR can be used to calibrate the yaw misalignment or drive the real-time yaw motions for wind turbines, which would improve the power-generation efficiency. The advantage of LiDAR utilization is that the accuracy of inflow wind measurement would be greatly improved, while its disadvantage is that the cost remains high and the data validity is not sufficiently high. In this paper, an efficient machine learning method for estimating LiDAR measurement is developed to establish the real-time yaw calibration framework and sustain the LiDAR rolling utilization. Firstly, the correlation of LiDAR measurement with SCADA features is analyzed to estimate LiDAR measurement using only SCADA data. Secondly, several machine learning algorithms are studied for performance comparison, and the dependence of each algorithm on data size is also analyzed. Experimental results show that, the proposed XGBoost algorithm has high accuracy, requires less data, and can quickly calibrate the yaw misalignment. Finally, the field testing is held for a commercial 2 MW wind turbine to verify the effectiveness. The field-test results show that the proposed method is feasible for industrial applications and can improve the annual theoretical power generation by 3.66% compared to the situation without calibration, which also provides an executable and economical solution for LiDAR replacement planning.

Оптимизация логистических маршрутов в целях сохранения безопасности поставки товаров в Российскую Федерацию в контуре параллельного импорта

In the context of economic uncertainty, it is difficult to control the business processes of organizations depend-ent on the import component in order to minimize risks in many (if not all) industries. Nowadays, the activities of organizations have become affected by negative factors, which include the implementation of sanctions policy by unfriendly countries, violation of foreign trade logistics routes, refusal of counterparties-importers to fulfill contractual obligations, withdrawal of foreign companies from the Russian market, and many others. Such phenomena as parallel imports, indirect and gray imports, new logistics chains and creative economic solu-tions have become a response to the challenges of the external environment. The aim of the article is to con-sider not only opportunities, but also limitations associated with the use of parallel import resources. In search of optimal solutions, an analysis of logistics routes for the supply of goods to the Russian Federation as part of parallel imports was carried out using the DEA (Data Envelopment Analysis – data convolution analysis) meth-od to confirm the effectiveness of individual directions. Delivery times, customs clearance costs, and the cost of transit through the EAEU were selected as input parameters, and rating, service, and supply volumes were se-lected as weekends.

An integrated bi-objective optimization model accounting for the social acceptance of renewable fuel production networks

Renewable liquid fuels produced from biomass, hydrogen, and carbon dioxide play an important role in reaching climate neutrality in the transportation sector. For large-scale deployment, production facilities and corresponding logistics have to be established. However, the implementation of such a large-scale renewable fuel production network requires acceptance by citizens. To gain insights into the structure of efficient and socially accepted renewable fuel production networks, we propose a bi-objective mixed-integer programming model. In addition to an economic objective function, we consider social acceptance as a second objective function. We use results from a conjoint analysis study on the acceptance and preference of renewable fuel production networks, considering the regional topography, facility size, production pathway, and raw material transportation to model social acceptance. We find significant trade-offs between the economic and social acceptance objective. The most favorable solution from a social acceptance perspective is almost twice as expensive as the most efficient economical solution. However, it is possible to strongly increase acceptance at a moderate expense by carefully selecting sites with preferred regional topography.

Shelf life enhancement technique of Musa acuminata in a controlled environment and optimization of process parameters affecting shelf life using genetic algorithm.

An economical and effective storage solution has been designed in this work for the storage of postharvest fruits and vegetables. Musa acuminata or banana has a shelf life of 5-6 days in open uncontrolled environment. This article reports a storage solution of M. acuminata in a controlled enclosure containing titanium oxide (TiO2 )-coated inner walls and irradiated with ultraviolet ray of band "C," an air filtration unit, 5% by volume potassium permanganate (KMnO4 ) solution in a clay pot, grow lights, and activated charcoal granules. The same fruit was kept in an uncontrolled environment too. The percentages of dark spots on banana (M. acuminata) upon storage in controlled and uncontrolled environments have been estimated using an image-processing algorithm. The prediction of dark spots was conducted using multi-linear and multivariate polynomial regression. Experimentation with optimum process parameters obtained with genetic algorithm resulted in a shelf life extension of 6 days as compared to its storage in an uncontrolled environment. The setup can be used in vegetable and fruit markets for the extension of shelf life of postharvest perishable items in a compact and cost-effective manner. The setup does not use any refrigeration process thereby decreasing energy requirement.

A critical review on contemporary power electronics interface topologies to vehicle‐to‐grid technology: Prospects, challenges, and directions

AbstractWith the evolution of the smart grid concept, the production of electric vehicles (EVs) is predicted to rise because of environmental concerns, technological advancements, and improvements in EV management. Vehicle‐to‐grid (V2G) is an enabling, realistic, and affordable technology to cope with a large number of EVs, increase energy sustainability, provide economical solutions, satisfy user‐side consumers, and facilitate power flow to the grid. Power electronics (PE) converters, particularly bidirectional power converters, are promising interfaces for V2G infrastructure because they determine the characteristics and functionalities of V2G. Therefore, this study provides an extensive review of the characteristics, technological aspects, and visions of V2G infrastructure. This review helps to identify the current state, most recent developments, and problems related to bidirectional interface topologies and control strategies in V2G infrastructure. It further examines the classification of chargers or dischargers based on numerous factors, including limitations and impacts. Furthermore, the benefits, challenges with possible mitigation solutions, and future outlooks in the implementation of V2G technology are discussed. This review is planned to serve as a reference for existing work in V2G frameworks, PE interfacing topologies, and control strategies, and to also facilitate a guideline for future work that can be implemented to flourish V2G technology.

Modeling and solving the multi-objective energy-efficient production planning and scheduling with imperfect maintenance activities

PurposeThe purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.Design/methodology/approachThis study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.FindingsThe computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.Originality/valueThis study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.