Energy Efficiency Indicators Research Articles

Optimization of marine hybrid power energy consumption

Abstract The energy and power system of the ship is the core of the ship, and the composite energy storage plays a great role in reducing the load power fluctuation of the ship, which effectively optimizes the energy efficiency index and reliability of the ship. [Objective] To better optimize the ship energy management system, a control model is established according to the characteristics of the energy system of hybrid electric ships. [Method] Energy consumption optimization is carried out by using a rule-based energy control strategy and energy control strategy based on equivalent fuel consumption minimum (ECMS). The dynamic control and strategy of the hybrid ship were optimized, and the data simulation and real ship application were carried out on the hybrid experiment platform. [Results] According to the data and results of the real ship application, the following results were shown: The daily fuel saving rate of the ECMS strategy is 14.6% in normal operating conditions and 13.3% in cruise operating conditions. [Conclusion] It has a great effect on the improvement of ship energy efficiency.

ЕФЕКТИВНІСТЬ ЕЛЕКТРОСПОЖИВАННЯ НА ГІРНИЧОРУДНИХ ПІДПРИЄМСТВАХ З УРАХУВАННЯМ ВИКИДІВ

The question of the efficiency of electricity consumption arises acutely at mining enterprises, since in modern conditions the extraction of minerals is largely determined by increased electricity consumption. Therefore, the value of the power consumption fluctuation indicator, which is not taken into account at such enterprises, should naturally be considered as emissions that lead to additional economic losses, that is, to a decrease in the efficien-cy of power consumption. Given that electricity consumption at mining enterprises is usually higher than the specified level, it is advisable to study the corresponding efficiency in the paradigm of the theory of random processes with the determination of emissions. The essence of the problems related to the study of electricity consumption involves the expediency of determining both the actual values of the relevant indicators and some of their normative values. To evaluate electricity consumption by industrial enterprises in general and mining enterprises separately, the "energy efficiency index" is used, which evaluates the loss of energy reserves. The indicator of energy efficiency can be measured through a coefficient, as a ratio of output results to input re-sources, or through the volume of production, its range. The purpose of the article is a statistical analysis of the efficiency of electricity consumption at mining enterprises, taking into account emissions. The research method-ology involves the use of mathematical methods, in particular the theory of probabilities, statistical methods. The content consists in the defined values of the intersection of indicators of electricity consumption by mining en-terprises corresponding to the given (planned) level. Emissions that disrupt the uninterrupted operation of the enterprise are analyzed in order to make appropriate management decisions. The scientific novelty consists in the application of statistical methods in the study of emissions in relation to electricity consumption as a random process. The practical value is in ensuring the possibility of increasing the efficiency of electricity consumption at mining enterprises based on the processing of the values of emission indicators.

Methods of reducing fuel consumption by seagoing vessels in order to reduce emissions of harmful substances into the atmosphere

The aim of the paper is to draw attention to the emissions of toxic compounds into the atmosphere problem by seagoing ships. Annex VI of the MARPOL Convention, which came into force in 2005, concern the prevention of air pollution from ships, forced shipowners to use solutions aimed at limiting the emission of these harmful substances into the atmosphere. One of the instruments enabling the implementation of these guidelines is the design energy efficiency index EEDI, introduced obligatorily for designed and newly built ships. In turn from 2013, the regulations also oblige shipowners to maintain an effective energy management plan during ship's operation, SEEMP (Ship Energy Efficiency Management Plan). The paper presents factors that influence the reduction of fuel consumption by ships, leading to a reduction in emissions of harmful substances into the atmosphere and thus achieving the required EEDI and other indicators. These are factors related to the ship's hull, the main propulsion engine and the propeller-rudder system. The influence of each of these factors on the level of fuel consumption by the ship was indicated. The work highlights the methods of reducing fuel consumption by seagoing ships aimed at reducing emissions of toxic compounds into the atmosphere, which are currently the most popular and effective, and relate mainly to the hull and main propulsion engines.

SHORT INTRODUCTION ON PRESENT DESIGN AND TRENDS REGARDING

This paper covers some aspects regarding present technology used in large crude oil carriers design and operation, as well as requirements regarding energy management on board. Obviously, due to complexity of such subject, there cannot be an exhaustive presentation. It is intended as a mere starting point for further discussion and research regarding possibilities to improve vessel’s general energy efficiency, including ways of using non-conventional and renewable energy, with due regard to specific trading routes involving large oil tankers. Some practical figures achieved typically on a Very Large Crude Oil Carriers engaged in international voyages are presented. A brief explanation on Energy Efficiency Index (EEI) and Carbon Conversion Factors (CF), as accepted by IMO, is also included. Work may be continued with further theoretical research in energy efficiency improvement on board such vessels. The article is structured in five parts: Introduction, Main Particulars of Large Tankers, Oil Tankers Outfitting, Energy Management Plan and Conclusion.

A dynamic migration route planning optimization strategy based on real-time energy state observation considering flexibility and energy efficiency of thermal power unit

New energy resources compromising intermittent and fluctuating natures have been integrated into the power grid on a large scale, and thermal power units are obliged to promote the depth of deep peak shaving and flexible response-ability to cope with this new scenario. The safety, flexibility, and high efficiency of coal-fired units are the ultimate goals of its transformation, and there is a mutual influence and mutual restriction relationship among these indicators. To exploit the flexibility of thermal power units, take into account efficiency and safety, and play a supporting role in the new power system, a control strategy that weighs various indicators needs to be developed. Based on heat flow model and dynamic state space model, and updated matrix in real time, the key process parameters affecting the flexibility of heat transfer can be fully characterized. By using the observed state and calculation, the load response index and the energy efficiency index are optimized under the boundary constraint. The results show that the multi-objective optimization methods can avoid over regulation, reduce the flue gas flow by 3.23%–3.59%, and reduce the fluctuation of state quantity under the premise of satisfying the load response rate, about 2.32%–2.52% away from the safety boundary of the design temperature parameter to achieve the flexibility of frequency modulation, high efficiency of energy transmission and operation safety.

Developing correction factors for weather’s influence on the energy efficiency indicators of container ships using model-based machine learning

The International Maritime Organization employs technical and operational indicators to assess ship energy efficiency. Weather conditions significantly impact ship fuel consumption during voyages, necessitating the consideration of this influence in energy efficiency calculations. This study aims to design models for estimating the impact of weather components on fuel consumption and develop correction factors to cope with the weather effect on the fuel consumption of container ships for different sea states. Using model-based machine learning, the study analyzes noon reports and hindcasted weather data from two sister container ships. It quantifies weather-induced fuel consumption across various sea states, ranging from 2% to 20%, with an average of 7%–13% depending on the model used. Correction factors specific to each sea state are derived, and different approaches for their integration into energy efficiency indicators are proposed. This study advocates tailored weather correction factors for energy efficiency metrics tied to specific sea states, emphasizing the need for standardized weather impact assessments. Prior to any formal policy application, future work is needed to address the limitations of the present study and extend this approach to various ship types and sizes and different geographical regions.

Effects of sowing date and nitrogen applications on the energy efficiency of facultative wheat (Triticum aestivum L.) in a Pannonian environment

Energy efficiency analysis provides a deeper understanding of non-renewable energy dependent cropping systems. In this study, we examined the crop yield and energy efficiency of facultative rainfed wheat (WW – winter wheat, WS – spring wheat) and mineral nitrogen (N) fertilization (0, 50, 100, 150, and 200 kg N ha−1) in two growing seasons 2019/20 and 2020/21 in Central Europe. WW out performed WS significantly overall (2019/20: +30.3 to +47.9 %; 2020/21: +18.9 to +37.3 %) in terms of energy efficiency indicators. The impact of N fertilization on energy efficiency was minimal, largely due to one dose application of mineral N fertilizer. The highest estimated net-energy output (NEO) was observed at 160.2 kg N ha−1, which may not sustainable for this pedo-climatic region due to potential N emissions risks. Zero N fertilization showed best performance in terms of energy use efficiency (EUE), energy intensity (EI), and energy productivity (EP). The ERG z-score, which combines NEO and EUE into a single bi-dimensional indicator, indicated an optimal N fertilization level of 72.0 kg N ha−1.

Exploring the Complexity of Energy Poverty in the EU: Measure it, Map it, Take Actions

AbstractEnergy poverty presents a pressing challenge in the European Union (EU), worsened by recent geopolitical events and economic vulnerabilities, particularly highlighted by the COVID-19 crisis. This article explores the complexity of energy poverty within the EU context, emphasizing the necessity to define, measure, and monitor it comprehensively. It reviews the evolution of energy poverty definitions and causes, underlining the multifaceted nature of the issue influenced by factors such as low-income, high-energy prices, and building inefficiencies. Various measurement indexes are examined, and categorized into consensus, expenditure-income comparison, and direct/indirect measurement indicators, offering insights into their advantages and limitations. Furthermore, the work discusses mapping methodologies to pinpoint instances of energy poverty spatially. It also examines best regulatory practices employed by nations, including economic accessibility enhancements and structural interventions like investments in energy efficiency and renewable sources. Finally, the authors propose a novel approach to map energy poverty at municipal granularity in Italy, integrating economic vulnerability and building energy efficiency indices.

A benchmark study on the energy efficiency and environmental impacts of alternative fuels in gulet-type sailing yachts

Gulet-type yachts are one of the symbols of maritime culture with their unique hull forms and schooner or ketch-type riggings. In parallel with the targets aiming for decarbonization in the maritime industry, energy efficiency and emission control are on the agenda for these types of yachts. Driven by this motivation, a novel benchmark study for the gulet-type yachts is conducted to evaluate the energy efficiency and environmental impacts associated with the adoption of LNG or methanol as primary fuel alternatives to MDO. The benchmark study is constructed in two steps: Presenting the design and propulsion characteristics of existing gulets, followed by a detailed analysis of the energy efficiency and environmental impacts of using alternative fuels. Therefore, 57 gulets with round and transom sterns whose hull forms are analyzed, modeled and general characteristics are presented. After modeling, the resistance and effective power of hull forms are predicted using the Holtrop-Mennen method and CFD. The flow characteristics around the hulls are obtained and the results are validated using the previous experimental studies in the first step. Then, installed and computed engine capacities are compared, and the Annual Emission Ratio and Energy Efficiency Index (EEI) are calculated for environmental impact assessments. Finally, the applicability of using LNG or MeOH-fueled propulsion systems for gulet-type yachts is discussed considering energy efficiency and design. According to the results, transitioning to alternative fuels can increase the Energy Efficiency Index of gulet-type yachts by over 20%.

Experimental comparison investigation on the performance analysis of desert crystal sand roses and sand grain as natural effective heat storage materials in conical solar distillers: 4E and sustainability analyses

Conical solar distillers represent one of the most important technologies for producing low-cost freshwater in remote areas. However, its drawback is its limited freshwater production due to heat loss, so the present study aims to use natural effective heat energy storage materials to reduce heat loss, improve productivity, and avoid the higher cost of producing freshwater. To achieve this goal, comparison investigations on the performance analysis of Desert Crystal Sand Roses and Sand Grain as natural effective heat storage materials in conical solar distillers to improve freshwater productivity and at the same time avoid the high cost of producing freshwater. To achieve this goal experimentally, three identical conical solar distillers were built and tested in El Oued, Algeria. The first is the classical conical solar distiller (CCSD). The second is the conical solar distiller with the Natural Desert Crystal Sand Roses (CSD-SR). The third is a conical solar distiller with the Natural Desert Sand Grain (CSD-SG). The experimental results demonstrated that incorporating the Desert Crystal Sand Roses as natural storage materials in the distiller basin represents an innovative design that is characterized by serving as corrugated surfaces to enhance the absorbed rates of solar rays and interface surface area with the basin water, in addition to representing effective heat energy storage materials. Where using the Desert Crystal Sand Roses (CSD-SR) increases the cumulative productivity to 9.29 L/m2 per day with an improvement of 95.58 % compared to CCSD. Also, the use of Desert Crystal Sand Roses (CSD-SR) improved the energy efficiency, exergy efficiency, and sustainability index by 94.45, 227.45, and 2.9 % compared to CCSD. Also, the exergo-economic analysis indicated that the annual energy and exergy outlets were 94.48 and 227.42 %, respectively. Additionally, the cost per liter of produced freshwater from CSD-SR was reduced by 48.61 % compared to CCSD.

METHODOLOGICAL APPROACH TO ASSESSING THE IMPACT OF ENERGY EFFICIENCY ON THE FINANCIAL PERFORMANCE OF A GAS COMPANY

Currently, the use of energy-saving technologies that reduce costs and improve the production process is the most important factor in the development of the gas industry. The relevance of the research topic is due to the fact that in order to resolve issues related to reducing energy costs in the gas sector of the Russian economy, optimal use of non-renewable energy resources, and reducing technological losses, an integrated approach to assessing energy efficiency is required, as well as a methodology for assessing the impact of energy efficiency indicators on the financial performance of a company. The purpose of this article is to develop a methodological approach to assessing the impact of the level of energy efficiency on the financial performance of a gas company. The research methodology is based on correlation and regression analysis tools. As part of the study, a system of energy efficiency indicators for a gas company's activities has been formed and, using correlation and regression analysis tools, a methodology for assessing the impact of the level of energy efficiency on the financial performance of a gas company is proposed. An algorithm for correlation and regression analysis is presented, which makes it possible to formalize a step-by-step assessment of the impact of the level of energy efficiency on the financial performance of a gas company. The proposed methodological approach allows us to identify correlation-regression dependencies between the company’s key performance indicators (sales revenue and net profit) and the proposed energy efficiency indicators, determine the most significant indicators that affect the company’s performance indicators and determine the equation for the relationship between the company’s performance and energy efficiency indicators. Testing of the proposed approach using the example of the gas company PJSC Gazprom made it possible to quantify how changes in the energy intensity of gas production and the energy intensity of gas transportation will affect changes in sales revenue and net profit of the company. It has been established that the energy efficiency indicator such as the specific energy intensity of gas transportation has the greatest impact on the financial performance of the company. Regression equations have been established to describe the nature of the relationship between energy efficiency indicators and sales revenue and net profit of a gas company.

Spatiotemporal trajectory of energy efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area and implications on the route of economic transformation.

The Guangdong-Hong Kong-Macao Greater Bay Area has attracted attention for its extraordinary pace of economic development and is considered to be leading the way in China's transformation from a manufacturing to an innovation cluster. However, due to rapid economic expansion and rapid urbanization, the Great Bay Area still struggles with low energy efficiency and environmental degradation, which has slowed down the pace of development. Therefore, in order to alleviate energy pressure, promote the country's sustainable development and gain a competitive advantage in the global market, researching energy efficiency and improving energy utilization efficiency is crucial. In this study, macro-level energy efficiency indicators are constructed using energy consumption data from various cities in the Greater Bay Area for the period from 2000 to 2020, and the spatio-temporal evolution of energy efficiency is analysed. The results show that all cities in the Greater Bay Area experienced an increasing trend in energy efficiency from 2000 to 2019, with significant variation in growth rates and magnitudes between cities. Compared to the nine cities in Guangdong province, Hong Kong and Macao exhibited significantly superior energy efficiency, with Foshan recording the highest growth rate of 14%. In 2020, most cities experienced a decline in energy efficiency due to the COVID-19 pandemic, with Macao experiencing the greatest decrease at 57%. Hong Kong and Macao are both in the "low consumption and high efficiency" target region, while Guangzhou, Shenzhen and Zhuhai are consistently in the "both high" region. Changes in the industrial upgrading index correspond significantly with changes in energy efficiency trajectories, with the transition from primary to secondary and tertiary industries playing a more substantial role. There is no significant association found between the strength of environmental regulation and changes in energy efficiency. The study's findings indicate that the most effective way to achieve economic transformation in the majority of China's regions is to combine adequate environmental legislation with industrial structural adjustment.

Energy efficiency and greenhouse gas emissions: A panel ARDL model of top five emitters in Africa

The Paris Agreement has mandated drastic decarbonization by developed and developing economies. Many of the top African emitters are now exploring drastic restructuring of the production processes in a way that promotes energy utilization efficiency. This is critical for ensuring an environmentally benign growth process. This study presents a unique addition to the body of existing knowledge by analysing the effect of some indicators of energy efficiency on three indicators of environmental quality among the top five emitters of GHG in Africa. The data were from the World Development Indicators (WDI), covering the 1990–2020 periods for South Africa, Egypt, Nigeria, Algeria, and Libya. The panel Autoregressive Distributed Lag (ARDL) model was used for data analysis. The results showed that all the included series were stationary at first difference. The optimum lag lengths were determined independently in STATA 17 software, and the most frequent lags across the countries were selected. The Hausman test revealed that the pooled mean group (PMG) estimation was preferred to other estimators. The results showed that in the long-run, particulate emission damages, CO2 intensity, and energy use intensity positively impacted GHG emissions, while GDP per capita and renewable energy utilization produced mixed results. In the short run, the error correction mechanism parameters were all significant (p < 0.01) in Libya for all emission indicators, while Algeria showed significance (p < 0.01) in total GHG and CO2 per capita models. The coefficient of particulate emission damages significantly reduced (p < 0.01) total GHG emissions in Libya and Nigeria and renewable energy significantly increased (p < 0.01) GHG emissions in South Africa but reduced them in Nigeria. Also, CO2 emission intensity significantly (p < 0.01) and positively impacted GHG emissions in South Africa, Egypt, Libya, and Nigeria, while electricity power transmission losses increased total emissions and CO2 emissions in Libya and Algeria. It was concluded that initiatives to reduce GHG emissions should focus on developing countries’ sensitivity to emission damages, and promotion of initiatives for using renewable energies. Also, promotion of energy efficiency across industries offers a prospect for ensuring environmental sustainability.

Investigating thermal performance and energy efficiency in under-floor air distribution data centers: A case study

This study conducted on-site measurements of air temperature and airflow velocity at the cold aisle outlet, combined with infrared imaging, to derive optimized layouts for rack servers. It was found that installing blind plates effectively improves the uniformity of cold air distribution within the racks, as indicated by the temperature and airflow velocity at the server inlet and outlet under both blind and non-blind plate conditions. Finally, thermal performance indicators (i.e., SHI, β, RHI, RCI) and Reynolds number were used to assess the thermal performance of the data center, while energy efficiency indicators (i.e., PUE, WUE, CUE) were employed to evaluate its energy efficiency. The results revealed that the cold aisle has less air distribution at both ends and is more concentrated in the middle. It is advisable to position high-power servers in the middle racks and place racks with relatively lower power at the front and rear ends to ensure effective heat dissipation of the servers. The installation of blind plates can effectively enhance the uniformity of airflow within the racks and improve server cooling. Among the tested racks, 16 out of 17 exhibited low temperatures (RCILO) below 90%, indicating heat loss and energy waste. The PUE value of the data center is 1.19, and the CUE value is 0.77.

Application of energy sustainability model based on optical sensing technology in intelligent warehousing performance management in green manufacturing industry

As the global focus on sustainable development continues to grow, green manufacturing, as a way to optimize resource use and reduce environmental impact, needs to be combined with advanced technologies to improve its efficiency. This study aims to explore the application of energy sustainability model based on optical sensing technology in smart storage of green manufacturing industry, evaluate its impact on storage performance management, and further promote the development of green manufacturing industry. In this paper, an optical sensing system is constructed to monitor and analyze the energy consumption in storage environment in real time. In this study, a green manufacturing enterprise was selected as an example, and the optical sensor was used to monitor energy consumption, inventory status and environmental parameters in real time to ensure the real-time and accuracy of data. The collected data is analyzed to identify patterns and anomalies in energy use to optimize inventory management and logistics scheduling. Evaluate the energy efficiency of storage systems by setting energy efficiency indicators and compare them with traditional models to quantify improvements. On the basis of monitoring and analysis, the energy management strategy is continuously adjusted to enhance the adaptability and flexibility of the intelligent storage system. The research results show that the application of optical sensing technology can significantly improve the energy management performance in warehousing, through real-time monitoring and intelligent optimization, enterprises can achieve more efficient energy use, further promote the implementation of green manufacturing, and provide strong support for the realization of environmental and economic benefits.

Methodological Solutions for Predicting Energy Efficiency of Organic Rankine Cycle Waste Heat Recovery Systems Considering Technological Constraints

Solving strategic IMO tasks for the decarbonization of maritime transport and the dynamics of its controlling indicators (EEDI, EEXI, CII) involves the comprehensive use of renewable and low-carbon fuels (LNG, biodiesel, methanol in the mid-term perspective of 2030, ammonia, and hydrogen to achieve zero emissions by 2050) and energy-saving technologies. The technology of regenerating secondary heat sources of the ship’s power plant WHR in the form of an Organic Rankine Cycle (ORC) is considered one of the most promising solutions. The attractiveness of the ORC is justified by the share of the energy potential of WHR at 45–50%, almost half of which are low-temperature WHR (80–90 °C and below). However, according to DNV GL, the widespread adoption of WHR-ORC technologies, especially on operating ships, is hindered by the statistical lack of system prototypes combined with the high cost of implementation. Developing methodological tools for justifying the energy efficiency indicators of WHR–ORC cycle implementation is relevant at all stages of design. The methodological solutions proposed in this article are focused on the initial stages of comparative evaluation of alternative structural solutions (without the need to use detailed technical data of the ship’s systems, power plant, and ORC nodes), expected indicators of energy efficiency, and cycle performance. The development is based on generalized results of variation studies of the ORC in the structure of the widely used main marine medium-speed diesel engine Wärtsilä 12V46F (14,400 kW, 500 min−1) in the operational load cycle range of 25–100% of nominal power. The algorithm of the proposed solutions is based on the established interrelationship of the components of the ORC energy balance in the P-h diagram field of thermodynamic indicators of the cycle working fluid (R134a was used). The implemented strategy does allow, in graphical form, for justifying the choice of working fluid and evaluating the energy performance and efficiency of alternative WHR sources for the main engine, taking into account the design solutions of the power turbine and the technological constraints of the ORC condensation system. The verification of the developed methodological solutions is served by the results of comprehensive variation studies of the ORC performed by the authors using the professionally oriented thermoengineering tool “Thermoflow” and the specification data of Wärtsilä 12V46F with an achieved increase in energy efficiency indicators by 21.4–7%.

МОДЕЛЮВАННЯ ЕНЕРГОЕФЕКТИВНОСТІ ЖИТЛОВОЇ БУДІВЛІ ЗА УМОВ РІЗНИХ ДЖЕРЕЛ ТЕПЛОВОЇ ЕНЕРГІЇ

The paper presents the results of modeling the process of energy consumption in public, residential, and commercial buildings as a result of the use of various sources of thermal energy. Buildings with such energy sources as: a) a low-temperature gas boiler with a capacity of up to 120 kW for the needs of heat supply of a residential building and freon air conditioning systems for the needs of cooling the building; b) a gas condensing boiler with a thermal capacity of up to 120 kW with a temperature regime of 55/45°C for heat supply and freon air conditioning systems for cooling; c) reversible heat pumping unit of the “ground-water” type with a temperature regime of 35/28°C for the needs of the heating and cooling system and a reversible heat pumping machine with a regime of 55/45°C for the needs of hot water supply; d) a reversible air-to-air heat pump for heating and cooling systems and electric boilers for hot water supply; e) a biomass solid fuel boiler with manual fuel loading with a heat output of more than 100 kW for heat supply and freon systems for cooling; f) a fuel pellet boiler with automatic mechanized fuel loading with a heat output of more than 100 kW for building heating and cooling and freon systems for cooling; g) centralized heating system of the building. The results of calculations of the specific primary energy consumption and specific greenhouse gas emissions for each of the above heat sources are presented. It is established that biomass boilers have the lowest values of primary energy consumption and specific greenhouse gas emissions. The lowest efficiency is achieved by a district heating system with a centralized energy source. The modeling was conducted for the climatic conditions of Vinnytsia. At the same time, the disadvantage of using solid fuel boilers is the limitation of their use in densely populated areas, which is explained by the complexity of flue gas cleaning and regular biomass supply. Therefore, it has been determined that the most efficient source of thermal energy for buildings of various types to achieve the standardized energy efficiency indicators is a ground-to-water heat pump system. This installation, along with providing buildings with thermal energy, allows for cooling in the warm season, operating in reverse mode.

Accounting for climate changes when constructing the Rossander graph

The temperature of the atmospheric air affects the design and indicators of energy efficiency of all elements of heat supply systems. An extremely important tool to develop heat sources that allows us to assess changes in consumer heat loads and model algorithms for heat source operation, taking into account the variability of outdoor air temperature in the geographical conditions of the design objects, is a graph of the duration of heat loads during the heating period (Rossander’s graph). It is impossible to construct the Rossander’s graph without data on the duration of the outdoor temperature standing during the heating period. In this paper, the problem of the lack of temperature data necessary for the construction of the Rossander’s graph in the current regulatory documents is revealed. The analysis of previous studies that produced temperature data with the duration of temperature standing is carried out, and the need for their refinement is substantiated. The arrays of hourly outdoor air temperatures were processed according to two weather models, as well as the array of average daily temperatures obtained as a result of measurements from the weather station for the geographical location of the main building of KNUCA. As a result of the comparative analysis, a model closer to reality was identified and, on its basis, actual data on the duration of outdoor temperatures standing for the city of Kyiv with a temperature step of 1℃ were developed. The obtained temperature data were compared with those that were developed in previous studies, as well as with the temperature data that are contained in the cancelled standard. The curve of the long-term run of the moving average outdoor air temperatures for the winter periods of 1973-2023 and its polynomial trend are constructed and compared with the curve that characterizes the run of the moving average five-year temperatures for the winter periods of 1861-1970 and its polynomial trend.

Integration of improved meta-heuristic and machine learning for optimizing energy efficiency in additive manufacturing process

Additive manufacturing (AM) has been a vital element of smart manufacturing. The high energy intensity or environmental sustainability issue of AM, however, has posed a great challenge to the future massive application, particularly laser-based direct energy deposition (L-DED). This study aims to determine the optimal processing parameters for energy-saving without compromising the geometrical appearance. A quantification model for energy efficiency at the process level was established, with two energy efficiency indicators of AM process. Then, a meta-heuristic Mayfly algorithm, augmented with Bayesian technique and mutation strategies, was proposed to improve hyperparameters in a typical machine learning model (XGBoost). Based on the full factorial L-DED experiments, this study compared the improved XGBoost with four types of XGBoost derivatives via four algorithm evaluation metrics. Non-dominated sorting genetic algorithm II was adopted to optimize the processing parameters subject to the constraints of geometrical appearance. Results indicated that the proposed algorithm outperformed other XGBoost derivatives in terms of prediction accuracy and convergence rate. The energy efficiency could be improved by 76.35 J/g or 6.78 % on average while ensuring the geometry of the deposited layers. This study could help enhance energy-efficient additive manufacturing via proper processing parameters selection and facilitate the sustainability in AM domain.

Traction Force, Sowing Quality, and Deformation Characteristics of the Coulter of a Grain–Fertilizer–Grass Seeder

The development of restoration technology and meadows, improvement of run-down pastures, and productivity improvement of old crops of perennial grasses is an urgent problem in agriculture. The tillage traction force in seeder designing and manufacturing is an important indicator of energy efficiency. The objective of this work is to reduce traction force and ensure seeding depth uniformity by justifying the optimal chisel parameters of a grain–fertilizer–grass seeder for direct seeding in sod. The Box–Behnken method was applied to investigate the traction force dependence on the seeder velocity, seed embedding depth, chisel width, and mounting angle. The obtained optimal parameters of coulters were justified by the finite element method. Structural and technological parameters were checked using the smoothed-particle hydrodynamics method on the deformation and wear of the seeder working body. The revealed optimal coulter parameters were as follows: chisel width was 20–20.97 mm, chisel length was 145–148.9 mm, mounting angle was 75°–81.6°, and achieved minimum traction force was 720 N. These parameters ensure the quality of grass seed embedding in the sod. The theoretical data of traction force (8.27–8.39 kN) are in accordance with the experimental (8.28–8.63 kN) data under field conditions. These findings are efficient in agrotechnical and mechanical predictions regarding the occurrence of chisel residual stresses and the working lifetime of the part.