Increased Energy Use Research Articles

An analysis of the rebound impact of energy consumption and the factors that influence it in China's agricultural productivity

With China's agricultural sector being a major contributor to both the national economy and energy consumption, the rebound effect—the phenomenon where energy efficiency improvements lead to increased energy use—poses significant challenges to sustainable energy use. The motivation for this study stems from the need to understand the extent of this rebound impact and its underlying drivers, particularly in the context of China's agricultural modernization efforts. This study examines the rebound effect of energy consumption in China's agricultural productivity and the factors influencing it over the period from 1990 to 2023. Using a Generalized Method of Moments (GMM) model, this research analyzes the relationship between energy consumption, agricultural productivity, and several influencing factors, including technological innovation, rural-urban migration, and financial development. The results reveal that (1) energy efficiency improvements have led to a significant rebound effect in China's agricultural sector, limiting potential energy savings, (2) technological advancements have mitigated the rebound effect to some extent, but the effect remains substantial, (3) rural-urban migration has contributed to labor shortages, increasing mechanization and energy demand, and (4) financial development has positively influenced both agricultural productivity and energy use, exacerbating the rebound effect. The study suggests that policymakers should focus on developing stricter energy efficiency standards and promoting technological innovations that reduce energy intensity in agriculture, while also addressing labor migration challenges to curb the rebound impact and achieve more sustainable agricultural growth.

The sufficiency-based, the de-growth, and the official – Critical remarks of the electricity chapter of the Hungarian national energy and climate plan based on a comparison to alternative scenarios

Hungary relies heavily on fossil and nuclear fuel imports from Russia. An urgent challenge is to develop a more sustainable and more independent energy system. There is a 2019 and a 2023 (draft) version of the National Energy and Climate Plan (NECP) but they arguably do not follow this direction. However, there are also alternative scenarios for Hungary that propose more comprehensive changes. This paper compares the targets proposed by the Hungarian NECPs to those proposed in two alternative studies: the sufficiency-based European-focused CLEVER (Collaborative Low Energy Vision for the European Region) scenario (created by a research team including 26 partner organisations from 20 European countries), and the de-growth-based “This Way Ahead” (TWA) scenario (which is the result of a Hungarian inter-university research, coordinated by the ELTE University's energy geography research group). A new element of this recent study is the simulation of hourly electricity supply and demand in these scenarios using EnergyPLAN to compare import requirements, potential surplus generation, and self-sufficiency. The review shows that the NECPs need to be reconsidered to increase the share of decentralized renewable electricity supply in a way that allows progress without increasing energy use and environmental burdens. Priority must be given to the rapid expansion of wind energy capacity by at least 10–20 times, which should be complemented by biogas-based flexible energy supply.

Scale-Dependent Effects of Urban Canopy Cover, Canopy Volume, and Impervious Surfaces on Near-Surface Air Temperature in a Mid-Sized City

Cities are significantly warmer than their surrounding rural environments. Known as the ‘urban heat island effect’, it can affect the health of urban residents and lead to increased energy use, public health impacts, and damage to infrastructure. Although this effect is extensively researched, less is known about how landscape characteristics within cities affect local temperature variation. This study examined how tree canopy cover, canopy volume, and impervious surface cover affect daytime near-surface air temperature, and how these effects vary between different scales of analysis (10, 30, 60, 90 m radii), ranging from approximate street corridor to city block size. Temperature data were obtained from a car-mounted sensor, with traverse data points recorded during morning, afternoon, and evening times, plotted throughout the city of Portland, OR. The variability in near-surface air temperature was over 10° F during each traverse period. The results indicate that near-surface air temperature increased linearly with impervious surface cover and decreased linearly with tree canopy cover, with canopy volume reducing the temperature by 1° F for every 500 cubic feet of canopy volume for evening temperatures. The magnitude of the effect of tree canopy increased with spatial scale, with 60 and 90 m scales having the greatest measurable effect. Canopy volume had a positive relationship on presumed nighttime and early-morning temperatures at 60 and 90 m scales, potentially due to the impacts of wind fluctuation and air roughness. Canopy cover still contributed the largest overall decrease in street-scale temperatures. Increasing tree canopy cover and volume effectively explained the lower daytime and evening temperatures, while reducing impervious surface cover remains critical for reducing morning and presumed nighttime urban heat. The results may inform strategies for urban foresters and planners in managing urban land cover and tree planting patterns to build increased resiliency towards moderating urban temperature under warming climate conditions.

Amplifying energy storage and production efficiency: Utilizing BaS3: Ni2S3: Sb2S3 synthesized from dithiocarbamate precursors for enhanced and sustainable energy solutions

During this period of increasing energy use, the scientific community and energy stakeholders have been closely monitoring electrochemical energy storage. In an attempt to enhance the functionality of charge storage devices, diethyldithiocarbamate ligand is employed as a chelating agent during the production of the novel BaS3: Ni2S3: Sb2S3. The semiconductor BaS3: Ni2S3: Sb2S3, which was made in an environmentally friendly manner, showed good photoactivity due to its 2.97 eV energy band gap and light absorption. The resultant chalcogenide had an average crystallite size of 19.69 nm and displayed outstanding crystallinity with mixed crystallographic phases. Furthermore, infrared spectroscopy was used to investigate metallic sulfide connections, and the findings indicated that they varied between 500 and 875 cm−1. This chalcogenide featured varied sites for electrochemical reactions due to its morphology. The electrochemical performance of BaS3: Ni2S3: Sb2S3 was assessed using a conventional three-electrode setup. With a specific capacitance of up to 1019.4 F g−1 and a power density of 11931.26 W kg−1, BaS3: Ni2S3: Sb2S3 has proven to be an excellent electrode material for energy storage. This remarkable electrochemical performance was further reinforced by the comparable series resistance (Rs) of 0.57 Ω. During electrocatalysis, the electrode produced an OER overpotential with a Tafel slope of 348 mV and 119 mV dec−1. In contrast, the overpotential and Tafel slope in terms of the HER activity and were 211 mV and 100 mV/dec, respectively.

Energy-economic-environmental analysis of bifacial photovoltaic thermal (BPVT) solar air collector with jet impingement

Jet impingement cooling enhances photovoltaic (PV) system efficiency by using high-speed fluid jets to reduce panel temperatures, improving performance and longevity. The effectiveness depends on factors like fluid flow rate, nozzle placement, and distance from the panel. While it boosts energy output, it may increase energy use for fluid circulation and add complexity to the system. This research explores a groundbreaking approach to enhancing the efficiency of bifacial photovoltaic thermal (BPVT) systems by integrating jet impingement technology. A novel design featuring a jet plate reflector is introduced, offering the dual benefit of cooling the PV panels while simultaneously reflecting light to optimize energy capture. The study comprehensively analyses the system’s performance, including energy output and a detailed techno-economic and environmental-economic evaluation. The modelling in this study was validated and reasonably consistent with experimental results. The system's output air temperature and thermal efficiency are 302.07–318.75 K and 33.83–62.28 %, respectively. The temperature and electrical efficiency range for PV systems are 304.39–339.54 K and 9.39–11.22 %. Reduced mass flow rate and increased solar irradiation are the most economically advantageous operating parameters for the proposed system, resulting in lower annual pumping costs and more significant annual energy gains for the system. CBR variations range from 0.1363 to 9.3445, with an average of 2. Additionally, by using BPVT with jet impingement to generate electricity rather than fossil fuels, it is possible to reduce annual carbon dioxide emissions by approximately 1.61 tons and save RM93.51 annually. In general, the proposed method should be used to minimize environmental pollution.

CNN-GRU-Attention Neural Networks for Carbon Emission Prediction of Transportation in Jiangsu Province

With the increasing energy use and carbon emissions in the transportation industry, its impact on the greenhouse effect is gradually being recognized. Therefore, this study aims to explore the achievement of carbon emission peak and carbon neutrality in transportation through prediction. The research employs a deep learning model, the CNN-GRU-Attention model, to predict carbon emissions in the transportation industry in Jiangsu, China. We select influencing factors through an extended STIRPAT model coupled with Lasso regression, and construct the CNN-GRU-Attention traffic carbon emission prediction model according to data indicators from 1995 to 2021. The model predicts carbon emissions from the transportation industry in Jiangsu Province between 2022 and 2035 under six distinct scenarios and proposes corresponding emission reduction strategies. The results show that the model in this study has higher prediction accuracy compared with other models, with a mean absolute error (MAE) of 0.061582, root mean square error (RMSE) of 0.085025, and R2 of 0.91609 on the test set. Scenario-based predictions reveal that emission peak in the transportation industry in Jiangsu Province can be achieved under the clean development and comprehensive low-carbon scenarios, with technological innovation being the primary driver of low-carbon emission reductions. This study provides a novel approach for forecasting carbon emissions from the transportation industry and explores the implementation path of emission peak through this method.

Configuration optimization and performance analysis of hybrid PV/wind systems in building groups

Distributed hybrid renewable energy is a promising technology for addressing environmental and energy issues, and its performance and system configuration play an essential role in the application. However, the contribution of energy sharing among buildings in building groups to the matching performance has yet to be fully explored. This study established a joint MATLAB-TRNSYS optimization model for the hybrid PV/wind building system to investigate the matching performance of energy consumption in building groups and energy production in PV/wind systems. The optimal system configuration for three objectives, technical, economic, and environmental, was also studied using the multi-objective particle swarm algorithm. Several factors influencing system performance and configuration were considered: renewable energy hybrid, a hybrid of different buildings, intensity of energy use and energy resource, and economic parameters. The results reveal that a hybrid system outperforms a single system, particularly a PV system with a smaller roof area and less installed capacity. Additionally, wind turbines contribute more to system performance than PV panels. Mixing buildings with different heights and functions could also improve system performance by renewable energy sharing in most instances, except multi-story office buildings. Increasing wind resources improves system performance more than solar resources, and increasing energy use intensity negatively impacts system performance for residential buildings but is beneficial for office buildings. Higher grid prices and feed-in tariffs can bring more economic benefits. This study revealed the contribution of energy sharing among different buildings, which could support better application of distributed hybrid renewable energy systems in complex urban environments.

What drives the relationship between digitalization and energy demand? Exploring heterogeneity in German manufacturing firms

The growing use of information and communication technologies (ICT) has the potential to increase productivity and improve energy efficiency. However, digital technologies also consume energy, resulting in a complex relationship between digitalization and energy demand and an uncertain net effect. To steer digital transformation towards sustainability, it is crucial to understand the conditions under which digital technologies increase or decrease firm-level energy consumption. This study examines the drivers of this relationship, focusing on German manufacturing firms and leveraging comprehensive administrative panel data from 2009 to 2017, analyzed using the Generalized Random Forest algorithm. Our results reveal that the relationship between digitalization and energy use at the firm level is heterogeneous. However, we find that digitalization more frequently increases energy use, mainly driven by a rise in electricity consumption. This increase is lower in energy-intensive industries and higher in markets with low competition. Smaller firms in structurally weak regions show higher energy consumption growth than larger firms in economically stronger regions. Our study contributes to the literature by using a non-parametric method to identify specific firm-level and external characteristics that influence the impact of digital technologies on energy demand, highlighting the need for carefully designed digitalization policies to achieve climate goals.

Multi-Objective Optimization of a Folding Kinetic Facade System Proposal for Thermal, Daylight, and Energy Performances

Efficient utilization of daylight and energy resources significantly influences the quality of indoor spaces, user comfort, and overall efficiency. This study presents a folding facade proposal through the design alternatives offered by kinetic architecture and parametric design to enhance efficiency. This alternative design method integrates and coordinates the design components simultaneously and makes any intervention easier when compared with traditional design methods. In this context, the method is based on computational models, aiming to find the most efficient design alternative by optimization. The proposed facade design specifically targets an indoor office space within a university. The modular system, integrated into existing windows, facilitates a folding movement. This dynamic feature aims to optimize illumination within the space, effectively controlling daylight without causing disruptions to users. Simultaneously, the design seeks to balance energy consumption and ensure thermal comfort. The results show that it provides a significant improvement over the base case. The proposed kinetic façade system improved indoor thermal comfort by 22.09-31.99% while slightly increasing energy use (2% at most). Although it provided an average of 59% improvement in spatial Daylight Autonomy (sDA), 13.30% - 87.38% was achieved compared to the base case. However, the desired value by LEED was achieved very little in Annual Sunlight Exposure (ASE). In conclusion, the proposed kinetic facade system proves to be a valuable intervention for enhancing the indoor environment of an office space at Dokuz Eylül University

A practical real-time control strategy for high-performance building HVAC operation concerning potential pandemic outbreaks in post-pandemic era

The lessons learned from the COVID-19 pandemic emphasize the need for building HVAC systems to be adaptable and prepared to adjust their operation for infection risk mitigation for future pandemics. Most guidelines suggest increasing outdoor air fraction in HVAC systems during pandemics. However, this approach is not energy-efficient due to the conditioning of additional outdoor air, and many practical systems face limitations in introducing more outdoor air than normal due to capacity or design constraints. Therefore, there is an urgent need for an alternative solution for HVAC system operation during pandemics that is energy-efficient, can effectively mitigate infection risks and does not require extensive retrofits to existing systems. To meet this need, this study proposes a practical real-time control strategy for high-performance HVAC operation in response to potential pandemic outbreaks. First, a supply air temperature (SAT) reset scheme for infection risk mitigation is proposed based on Mamdani fuzzy inference theory. Then, a coordinated control scheme is proposed to coordinate SAT reset with chilled water temperature adjustment for energy-efficiency enhancement. This strategy does not require system equipment retrofits but only changes in control logic to transition to pandemic operation. The effectiveness of the proposed strategy is validated in a high-fidelity Modelica-based simulation environment under various weather conditions. Results show that, compared to normal operation, the proposed strategy can significantly reduce new infection cases by 32∼46 % without increasing energy use, and may even achieve slight energy savings of 9∼13 %, while maintaining expected occupant comfort.

Solutions for decarbonising urban bus transport: a life cycle case study in Saudi Arabia

With heavy reliance on fossil fuels, countries like Saudi Arabia face challenges in reducing carbon emissions from urban bus transportation. Herein, we address the gaps in evaluating proton-exchange membrane fuel cell buses and develop a globally relevant life-cycle assessment model using Saudi Arabia as a case study. We consider various bus propulsion technologies, including fuel cell buses powered by grey and blue hydrogen, battery electric buses, and diesel engines, and include the shipping phase, air conditioning load, and refuelling infrastructure. The assessment illustrates fuel cell buses using blue hydrogen can reduce emissions by 53.6% compared to diesel buses, despite a 19.5% increase in energy use from carbon capture and storage systems. Battery electric buses are affected by the energy mix and battery manufacturing, so only cut emissions by 16.9%. Sensitivity analysis shows climate benefits depend on energy sources and efficiencies of carbon capture and hydrogen production. By 2030, grey and blue hydrogen-powered fuel cell buses and battery electric buses are projected to reduce carbon emissions by 19.3%, 33.4%, and 51% respectively, compared to their 2022 levels. Fully renewable-powered battery electric buses potentially achieve up to 89.6% reduction. However, fuel cell buses consistently exhibit lower environmental burdens compared to battery electric buses.

Unraveling the impact of energy demand and exports on environment and economy: A case study of South Asian Economies

<p class="MsoNormal" style="margin-top: 10pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">This study employs empirical analysis using an econometric model that examines the interdependence among environmental degradation, exports, and economic development with energy use. It also provides an environmental Kuznets curve (EKC) for selected South Asian economies utilizing time-series data. The findings reveal a long-term, stable equilibrium link between energy demand and pollution. There exists a positive relationship between structural factors and pollution. Moreover, this study constructs a model of exports and pollution from an interdependent perspective. The three perspectives are tested: the scale and structure of energy consumption considering the twin constraints of export-trade and pollution, and the scale of pollution in export-trade constraint. These results show that the increase in energy use leads to higher CO2 emissions amidst export volume. However, in the presence of income, the scale of effect lowers a little. The analysis also supports the presence of Kuznets curve for south-Asian economies. The results imply substantial scope for development in the energy use and pollution structure within South Asia's current export trade process. This development can be attained by regulating energy use and enhancing system efficacy without necessitating changes to the scale effect or structural effect.</span></p>

Autonomous Thermal Modulator Based on Gold Film‐Coated Liquid Crystal Elastsomer

AbstractRadiative cooling has been recently intensively explored for thermal management and enhancing energy efficiency. Yet, traditional materials with singular emissivity fall short in dynamic thermal management, highlighting the need for materials that can adjust their thermal radiation in real time. Active modulation methods, requiring external stimuli such as mechanical stretch, electric potential, or humidity change, offer adaptability but can increase energy use and complexity. Passive approaches, using materials' inherent thermal‐responsive properties, face manufacturing and scalability challenges. Here, a scalable yet effective passive approach is introduced for adaptive thermal modulation based on gold (Au) and liquid crystal elastomer (LCE) with a reversible response to environmental temperature changes. This modulator enables a “low thermal resistance” state through actuation‐induced microcracks that expose a high‐emissivity polymer substrate, and a “high thermal resistance” state by closing these microcracks and forming a high thermal resistance air gap between the modulator and the target object. The flexible design and fixed external dimensions of the Au‐LCE thermal modulator make it adaptable to various surface geometries. Furthermore, by adjusting the LCE's chemical composition, the modulator's transition temperature can be tailored, broadening its applications from enhancing building energy efficiency to improving clothing thermal comfort.

Malnutrition in Acute Stroke: An Article Review

The prevalence of malnutrition after stroke varies widely. It is estimated about one-fifth of patients with acute stroke are malnourished on initial hospital admission, while the prevalence of malnutrition ranges from 6.1 to 62%. Energy requirements increase due to stress caused by stroke, while food intake decreases due to impaired ability to eat, so the body will use its fat and protein stores as fuel to produce glucose. Muscle and fat tissue undergo degradation due to the breakdown of amino acids to form energy. Systemic consequences occur after stroke, peripheral immunodepression in association with overstimulation of the autonomic and neuroendocrine systems. Damage to cerebral tissue can activates the hypothalamus-pituitary-adrenal axis, resulting in increased levels of glucocorticoid hormones, catecholamines, and glucagon, leading to hypermetabolism (increased energy use), hypercatabolism (increased protein breakdown), and persistent hyperglycemia. The prevalence of malnutrition increases with the length of stay and decreased functional improvement during rehabilitation. Malnourished patients with stroke experience a higher stress reaction, which increases the occurrence of peptic ulcers, and infections of the respiratory and urinary tracts, thus extending the length of stay and increasing mortality.

Testing the Nonlinear Long- and Short-Run Distributional Asymmetries Effects of Bitcoin Prices on Bitcoin Energy Consumption: New Insights through the QNARDL Model and XGBoost Machine-Learning Tool

This study investigates the asymmetric impacts of Bitcoin prices on Bitcoin energy consumption. Two series are shown to be chaotic and non-linear using the BDS Independence test. To take into consideration this nonlinearity, we employed the QNARDL model as a traditional technique and Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) as non-conventional approaches to study the link between Bitcoin energy usage and Bitcoin prices. Referring to QNARDL estimates, results show that the relationship between Bitcoin energy use and prices is asymmetric. Additionally, results demonstrate that changes in Bitcoin prices have a considerable effect, both short- and long-run, on energy consumption. As a result, any upsurge in the price of Bitcoin leads to an immediate boost in energy use. Furthermore, the short-term drop in Bitcoin values causes an increase in energy use. However, higher Bitcoin prices reduce energy use in the long run. Otherwise, every decline in Bitcoin prices leads to a long-term reduction in energy use. In addition, the performance metrics and convergence of the cost function provide evidence that the XGBoost model dominates the SVM model in terms of Bitcoin energy consumption forecasting. In addition, we analyze the effectiveness of several modeling approaches and discover that the XGBoost model (MSE: 0.52%; RMSE: 0.72 and R2: 96%) outperforms SVM (MSE: 4.89; RMSE: 2.21 and R2: 75%) in predicting. Results indicate that the forecast of Bitcoin energy consumption is more influenced by positive shocks to Bitcoin prices than negative shocks. This study gives insights into the policies that should be implemented, such as increasing the sustainable capacity, efficiency, and flexibility of mining operations, which would allow for the reduction of the negative impacts of Bitcoin price shocks on energy consumption.

Performance Investigation and Optimization of Composite Materials in Household Dehumidifiers

The efficiency of household dehumidifiers is affected by air temperature and the temperature used for regeneration. A regeneration temperature that is too high can lead to increased energy use, heat build-up in the desiccant wheel, and lower dehumidification efficiency. In this study, we developed a LiCl@Al-Fum composite material and evaluated it through physical characterization and module testing. The results show that the LiCl@Al-Fum composite with a 20% mass fraction is particularly effective as a desiccant material. Additionally, a 15% volume concentration of neutral silica sol was identified as the optimal binder concentration. A comparative analysis of the effects of glass-fiber desiccant wheels (GF DWs), aluminum desiccant wheels (Al DWs), and commercial desiccant wheels (CM DWs) on household dehumidifier performance revealed that the Al DWs outperformed the CM DWs, showing a 13% improvement in the dehumidification rate and a 12.56% increase in the DCPP. An increase in the dehumidifier structure led to increases in the dehumidification rate by 11.8%, 11.9%, and 10% and in the DCPP by 11.6%, 12.1%, and 10%, respectively. Moreover, the modifications resulted in a 3.85 °C, 3.34 °C, and 3.8 °C decrease in the temperature.

Water-energy trajectories for urban water and wastewater reveal the impact of city strategies

The global water industry has a greater emphasis on energy management than ever before. The confluence of rising energy demand and costs, and net-zero greenhouse gas emission targets means the sector must rapidly transition to a new ‘energy future’. Yet, few cities have assessed the long-term energy use of their water and wastewater systems. Here, we undertake a novel and integrated assessment of the historical trends of energy use for water and wastewater in three Australian and two US cities, collectively 17 million people. The key research question is what were the historical trends of energy use for water supply and wastewater treatment, and what can we understand about the drivers? The research contributes a first systematic time-series assessment of energy trajectories of both water and wastewater, across multiple cities. Uniquely, it integrates long-term (up to 20 years) energy dynamics in a comparative analysis. The work also contributes a qualitative analysis of driving factors behind the observed energy variations. The time-series analysis (2001−2020) identifies how energy use is evolving through time in widely differing climate, urban and water infrastructure conditions. The cities studied demonstrated downward trends in water use by 30–42% and wastewater collected by 5–30%, primarily due to water conservation and drought-related restrictions. Annual per-capita energy use for water supply reduced in Los Angeles (−58%, from 276 to 116.5 kWh/p/a), San Diego (−59%, from 503.7 to 204.2 kWh/p/a), Sydney (−26%, from 40.6 to 30.1 kWh/p/a) and increased in Melbourne (+859%, from 15.7 to 150.6 kWh/p/a) and Perth (+139%, from 118.1 to 281.9 kWh/p/a). Compared to water supply, energy use for wastewater was far more stable (it varied between 45 and 85 kWh/p/a), and not the crucial contributor to overall energy use dynamics. The significant increase in seawater desalination is identified as the primary driver of increased energy use in the three Australian cities. To offset this huge demand, developing renewable energy generation emerged as the key strategy. It causes high fluctuation of renewable energy use shares (Sydney: 317 GWh, accounting for 48.5% energy use for water and wastewater in 2011; compared to 19 GWh, accounting for only 2.5% in 2008). In contrast, both Los Angeles and San Diego managed to considerably reduce energy use by decreasing their imported water volume and energy intensity (the result of an adjusted supply portfolio). However, the absence of consistently comprehensive water/energy/renewable energy data remains a significant hurdle for a thorough quantitative analysis of drivers. Given these observations, it is evident that detailed quantitative analysis for influencing factors (e.g. water use, climate, infrastructure upgrading, sustainability targets), requires separately reported energy use for both water supply and wastewater, reported water from categorized sources and significant other data. By addressing these issues, we can have a clear path towards an energy-efficient, sustainable urban water system with net-zero emissions.

Advancements and challenges in BaTiO3-Based materials for enhanced energy storage

Numerous researchers worldwide have been motivated to develop highly effective, environmentally acceptable green energy sources as a result of the recent sharp increase in energy use and the need for low emission levels. The energy generated from various renewable sources can be stored efficiently with a system that has a high energy density and high energy efficiency. Due to their enhanced dielectric, ferroelectric, and breakdown strength characteristics, BaTiO3 based dielectric/ferroelectric ceramic materials have received a lot of interest for energy storage applications in the past tw decades. In the present work, a thorough analysis of recent advancements in composites and single-phase BaTiO3 materials with enhanced energy storage performance. This review's main focus is on the crucial tactics and theoretical frameworks for improving the energy efficiency and recovered energy storage density of various BaTiO3-based materials. A thorough summary has been provided with the most recent developments in BaTiO3 based materials for multi-layered ceramic capacitors (MLCCs), pulse power capacitors, piezoelectric transducers, energy harvesting, electric vehicle batteries, and high-power electronic devices in order to confirm the commercial applications of BaTiO3 based single phase as well as multi-phase layered structures and composites.

ON THE RELIABILITY AND MAINTAINABILITY OF INDIVIDUAL ELEMENTS OF GAS DISTRIBUTION SYSTEM VALVES

At the current stage of the development of society, including in our country, there is an accelerating urbanisation process. The increasing role of cities in the country’s development, on the one hand, contributes to social, scientific, and technical development, and on the other hand, creates new economic, ecological, informational, social, and other challenges. One of the features of urbanisation is the increase in energy use. One of the primary sources of energy is natural gas. Transportation of natural gas from deposits and gas storages and its distribution to consumers occurs with the help of gas transportation systems. One of the components of gas transportation systems is gas distribution systems. They have a broad range of components and elements and a long list of requirements for the conditions of their manufacture, operation, and repair, and they are under the influence of numerous external factors. Such multivariability necessitates the development of specific models, methods, and information technologies for monitoring their state in conditions of uncertainty to solve the problems of forecasting and planning repair work on gas transportation systems. During the study, we determined the main factors affecting the reliability of gas pipelines overall. We also analysed the operational characteristics of the shut-off valves of elements of gas distribution systems, typical malfunctions, and the main features of its diagnosis and repair. During operation, gas distribution system elements are under the influence of many factors that affect their reliability. Considering all the factors arising at different stages of the life cycle of the gas distribution system elements will ensure their operational reliability, indestructibility, and durability. The results of the analysis of individual parameters of shut-off fittings of gas distribution systems are applicable for creating models and methods of monitoring, forecasting, and planning repair work on gas transportation systems under conditions of uncertainty. Keywords: shut-off valves, models and methods of monitoring, reliability, repair, defects.

The Influence of Surrounding Tall Buildings on Increasing Energy Use in BRI II Tower Jakarta

Jakarta has many tall buildings with office functions. This high-rise office building has been built since the 1970s and is still used today. This long-used building will experience a decrease in performance so that the high use of energy in the building, especially air conditioning and have an impact on increasing temperature on the environment. Retrofit is one way to improve building performance and reduce environmental impact. This study aims to take into account the influence of the environment on energy use as input for retrofitting. With retrofits carried out on a large number of high-rise office buildings, it is expected to reduce the impact of heat on the environment so as to support the Sustainable Development Goals on affordable and clean energy and climate action. With the simulation method using energy plus software, environmental influences will be simulated on the addition of heat that occurs in buildings.