Change In Coefficient Research Articles

Liquid-Water Transfer Coefficients of Porous Building Materials Under High-Humidity Conditions

The moisture transfer coefficient is a key parameter for analyzing the moisture-based physical properties of materials and studying the heat–moisture coupling process within building envelopes. The liquid-water transfer coefficient, as an important aspect of this process, plays a significant role, especially under high-humidity conditions. However, the global research on liquid-water transfer coefficients is still far from complete. To further enhance the research on liquid-water transfer coefficients, this study conducted capillary water absorption experiments on seven traditional and new porous building materials, focusing on testing the moisture transfer coefficients, primarily the liquid-water transfer coefficient. A novel analysis regarding the impact of sealing materials was proposed, based on the experimental results. Based on the experimental data, the concept of a critical value related to the variation in the capillary moisture content and the liquid-water diffusion coefficient was raised, and, building upon traditional empirical models, a completely new computational model was proposed. Data processing was carried out using methods such as variability analysis, correlation analysis, and nonlinear regression for model fitting. The research findings indicate the following: (1) The capillary water absorption rate and capacity of a material are influenced by its density and porosity. (2) In terms of sealing materials, self-adhesive films performed better than non-adhesive films. (3) The concept of critical capillary moisture content was proposed, based on the rate of change in the liquid-water diffusion coefficient. For the threshold of w ≤ 80%, a new calculation model with a higher correlation coefficient was proposed which can meet the calculation requirements of the diffusion coefficient under the vast majority of relative-humidity conditions.

Understanding Ion-Specific "Hofmeister" Effects in Enzyme Catalysis Through Using RNase A as a Paradigm Model.

Biophysical studies in the last two decadesdemonstratethat salts affect biomolecules in an ion-specific manner. Diverse biological processes such as protein folding, protein precipitation, protein coacervation and phase separation, and protein oligomerization,all showthat this ion specificity directly relatesto how individual ions interact with biomolecular surfaces. Interestingly, although ion-specific effects upon enzyme catalytic processes are well-known in the literature, a molecular level description of these effects is not yet available. This workaddresses this need by investigating ion-specific effects upon the enzymatic activity and stability of RNase A. We have developed a robust framework to analyze and quantify ion-specific effects upon the RNase A catalyzed phosphate ring opening reaction of cCMP.Both the folding thermodynamics and the Michaelis-Menten kinetic parameters of this enzyme show ion-specificity. However, these effects are not necessarily directly related to each other. Ion-specific effects observed in protein folding reflects mostly how an individual ion interacts with the overall protein surface; while alternatively, ion-specific effects on enzyme activity indicate how a given ion interacts with the enzyme active site surface or alternatively, how ions interact with the substrate molecule as represented by changes in the substrate thermodynamic activity coefficient.

Rotordynamics of a Single-Stage Brush Seal in Isolation: The Effects of Variable Stiffness and Back Plate Geometry

Abstract Brush seals control leakage around rotating components from areas of high to low pressure inside turbomachinery. They are known to contribute to the overall stability of gas turbines, therefore their dynamic behavior is of particular importance to engine designers. Despite this, limited research exists in the literature on the rotordynamic behavior of brush seals. This paper aims to experimentally characterize the leakage and rotordynamic performance of two seals with different bristle diameters tested with both conventional and pressure-relieved back plates with a slight interference. A dynamic test facility was utilized to study the dynamic characteristics of an isolated seal with changes in excitation frequency, rotational speed, and pressure drop. Seal leakage increased with bristle diameter and with the use of the pressure-relieved back plate but reduced with increasing rotational speed for all tests. The direct dynamic coefficients were shown to increase with pressure difference. The back plate geometry influenced the change in stiffness coefficient with rotational speed. The larger bristle diameter resulted in a stiffer seal, however, the damping coefficient reduced with the reduction in packing density. The insight provided by these results will help inform engine manufacturers on the suitability of implementing brush seals in future gas turbine designs.

Study on the effect of hydrogen cycle pressure relief time on the hydrogen permeability and mechanical properties of polyamide liner materials for type IV hydrogen storage cylinders of HFCVs

Plastic liners for type IV hydrogen storage cylinders of hydrogen fuel cell vehicles (HFCVs) experience varying pressure loads, deteriorating both hydrogen permeability and mechanical properties and impacting cylinder safety. This study performs hydrogen cycle tests on polyamide 6 (PA6) and polyamide 11 (PA11) samples (temperature: 288 K; pressure relief times: 6, 60, 3600 s; upper/lower pressure limits: 70/1 MPa). After 50 hydrogen cycles with 60 and 3600 s relief times, PA6 and PA11 exhibit changes in hydrogen permeability coefficients within 2%. However, with a 6 s relief time, the coefficients significantly decrease (>10%). After 6 s cycles, PA6 exhibits tiny holes, while PA11 exhibits clustered pieces of holes. Cracks appear in both materials' internal structures after 60 s cycles. Despite minimal tensile strength changes (within 5%), the nominal strain at tensile fracture of both materials changes significantly under different times. These findings can help determine optimal pressure relief times for hydrogen cycle tests on plastic liners.

High Spatial Resolution Neutron Imaging of Lithium-Ion Batteries: Correlating Microstructure and Lithium Transport

With the increasing desire for fast charging capabilities in lithium-ion batteries due to the popularity of electric vehicles, research has recently been focused on increasing energy and power density while simultaneously revealing the need for improved safety mechanisms and decreased overall cost. In response to this need, interest in thick battery electrodes has increased. By increasing the active material per unit area within the electrode, the energy density is increased due to minimization of current collectors, separators, and other packaging components. However, increasing the thickness of electrodes introduces new challenges, including charge-transport limitations.To successfully address the desired increase of energy density and capability of fast charging, high spatial resolution in operando neutron radiography (nR) was utilized to better understand the correlation between microstructure and lithium transport of ultra-thick electrodes. This allows for a comparison between the electrochemical processes occurring during cycling and what is seen in neutron imaging, bridging the gap between microstructural observation and electrochemical testing. Two differing fabrication methods were used to prepare the cathodes and anodes: a solvent free method using a hydraulic press and a wet cast method using N-methyl-pyrrolidone solvent (NMP). The fabrication methods were purposefully chosen to yield differing electrode microstructures. The lithium-ion batteries used in this work were fabricated using graphite (graphite (90 wt%): carbon black (5 wt%): polyvinylidene fluoride (5 wt%)) anodes and NMC (Li(Ni0.8Mn0.1Co0.1)O2) (80 wt%): carbon black (10 wt%): polyvinylidene fluoride (10 wt%)) cathodes with a thickness of ~2.5mm and diameter of 10mm. A deuterated electrolyte (1M LiPF6 EC/DMC=30/70 (v/v)) was used in order to improve the attenuation of lithium within the electrodes. Custom cells were fabricated using PFA Swagelok components to avoid any unnecessary neutron attenuation during neutron radiography. High-resolution (7.5 µm pixel size) in operando nR was performed on these cells using the Multimodal Advanced Radiography Station (MARS) beamline at the Oak National Laboratory High Flux Isotope Reactor. High spatial resolution neutron tomography (nCT) was performed on a cycled battery following in operando nR.Comparing changes in the attenuation coefficient for both a solvent free anode and wet cast anode reveals distinct lithiation patterns in each electrode. In the solvent free sample, there is a dense, but thin, lithium rich region near the separator. In the wet cast sample, the lithium distribution is more evenly dispersed through the thickness of the electrode. The difference in distribution is likely due to the different average pore size of the samples, as represented by the size distribution of macroscopic porosity (pore radius > 20 µm) observed from high resolution nCT. From a comparison of the macroscopic pore radius for each fabrication method it is clear that the solvent free method yields smaller pores and an increased number of pores, whereas the wet cast method yields larger pores and a decreased number of pores. Results from in operando nR during electrochemical cycling and ex situ high spatial resolution nCT on cycled electrodes show that lithium distributions and plating risks are shown to be controlled by both the macroscopic structure of the electrodes and the network of pores and microscale active areas that support electrochemical reactions. This research used resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory.

Dynamic performance assessment of offshore wind structures based on root morphology model

Assessing the dynamic performance of offshore wind turbines (OWTs) is crucial for their safe operation and maintenance. To evaluate the structural dynamic performance, traditional methods rely on the reanalysis of damage models, leading to the lack of the real-time capability. Therefore, this paper presents a structural dynamic performance assessment technology based on the root morphology model to address such issue. The approach is developed to synergize data fusion-based and environmental condition classification-based dynamic performance assessment technologies. The data fusion-based method, using optimized VMD for denoising and ARMA models for free response signals, enables real-time dynamic performance assessment by tracking changes in AR coefficients over time. In parallel, the environmental condition classification-based method employs wind speed and wave height monitoring data to classify structural response data into multiple healthy sub-databases. Subsequently, Extenics is applied to compute the correlation between the data to be evaluated and the performance state levels based on the classified data, providing a precise evaluation of the structural dynamic performance. Finally, these two technologies are integrated through root morphology models, which fully consider structural vibration response data and environmental monitoring data. To verify the real-time and reliability of the proposed method, field study has been carried out on a 4 MW monopile OWT during the passage of Typhoon 'In-fa'. Results indicate that the root morphology model-based assessment technique effectively evaluates the impact of typhoons on the dynamic performance of OWTs. Further, a rose diagram for the dynamic performance assessment of OWTs is drawn to achieve real-time evaluation of OWT dynamic performance, which has certain engineering significance to guarantee the safe operation of OWTs and reduce the cost of operation and maintenance.

BBCEAS-HLPC measurements for synthetic antioxidants (TBHQ, BHA, and BHT) in deep-UV region below 300 nm

This study investigates the integration of Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS) with High-Performance Liquid Chromatography (HPLC) to detect synthetic antioxidants; BHA, BHT, and TBHQ in the deep-UV region below 300 nm. The research addresses the need for more sensitive and cost-effective detection methods in HPLC systems, particularly for low analyte concentrations, by exploring BBCEAS as a superior alternative to conventional detectors that often fall short in sensitivity. The sensitivity of the HPLC-BBCEAS system is assessed by calculating the minimum detectable change in the absorption coefficient (αmin) and comparing with those obtained using conventional HPLC and single-wavelength HPLC-CRDS methods. The findings demonstrate that the HPLC-BBCEAS system achieves αmin values of 1.8 × 10−5 cm−1 for BHA, 2.8 × 10−5 cm−1 for BHT, and 1.9 × 10−5 cm−1 for TBHQ at 280 nm, with Limits of Detection (LOD) and Quantification (LOQ) up to 30 times lower than conventional HPLC systems.

Evaluating the impact of post-processing on the wear and friction properties of polyamide 6 carbon fiber composites produced by fused deposition modeling

The current research addresses the challenges encountered in polyamide 6 carbon fiber composites synthesized by fused deposition modeling. It specifically investigates issues such as inadequate interlaminar bonding and increased void content compared to conventionally manufactured composite components and as-built printed parts. The study focuses on printing pin samples via fused deposition modeling and explores various thermal post-processing methods to reduce void content while preserving dimensional accuracy. To evaluate wear and friction behavior, a pin-on-disc tester was used to test both as-built samples and samples post-heat-treated at 70 °C, 140 °C, and 210 °C. The results indicate that as the applied load increases from 5 to 20 N, both wear rates and friction coefficients increase across all speeds (1–5 m/s). Heating the samples to 70 °C and 140 °C strengthens the interlayer bonding. This significantly improves the maximum wear rates and friction coefficients compared to the as-built samples. However, samples heated to 210 °C do not show much of a change in wear rates or friction coefficients. Samples heated to 210 °C exhibit a decrease in wear rate of 16.87%, 15.82%, and 15.73% for loads ranging from 5 to 20 N, at speeds of 1, 3, and 5 m/s, respectively. This is likely due to pores sealing off and structures binding tightly. The worn surfaces were analyzed using a scanning electron microscope and measured the Shore D hardness of the samples before and after wear testing and documented the results for further analysis. In a scanning electron microscope, samples treated at 210 °C displayed smoother, less worn surfaces. Shore D hardness tests revealed a slightly higher hardness in samples heated to higher temperatures, followed by higher loads and sliding speeds in tribometer tests. This showed that the material was more stable. These post-processing methods significantly advance the development of functional composite elements for superior structural or dynamic performance.

Modeling solar power plants with daily data using genetic programming and equivalent circuit

AbstractAmong the various methods proposed for modeling solar panels, those based on equivalent circuits have received significant attention. In these approaches, determining unknown parameters varies depending on the modeling objective. To model voltage–current characteristics, circuit analysis methods are employed to extract these unknown parameters. However, this modeling method relies on data provided by the solar panel manufacturer, leading to increased modeling error over time as coefficients change. In this article, a method independent of the manufacturer's data for modeling solar panels is presented. This method enables accurate modeling of pre‐installed solar power plants. By utilizing genetic programming on a single day's worth of data from a solar panel, the proposed method can establish relationships with a high degree of fit for the open‐circuit voltage, maximum power point, and short‐circuit current based on weather conditions. Through these relationships, the voltage–current characteristics can be modeled with greater precision compared to traditional circuit analysis methods, and without the need for data from the solar panel manufacturer. Finally, for further evaluation, a 3 kW solar power plant is modeled, which demonstrates the effectiveness of the proposed method.

The effects of previous detoxifications on intelligence, speed, attention, and executive functioning in patients with moderate to severe alcohol use disorder.

Repeatedly undergoing supervised, medical, detoxification from chronic alcohol use may contribute to impairments in neurocognitive functioning of patients with an alcohol use disorder (AUD). Unsupervised, non-medical, detoxification, however, may also contribute to neurocognitive impairments, given the absence of first choice prescription medication to counteract severe withdrawal effects. So far, findings from previous studies are inconclusive and specifically effects of non-medical detoxifications are not investigated yet. Using an association modeling approach, this study investigates whether intelligence, speed, attention, and executive functioning are influenced by previous medical and/or non-medical detoxifications. A total of 106 participants with AUD underwent a clinical medical supervised detoxification. Basic characteristics of the patient were recorded including the number of previous medical and non-medical detoxifications. Neuropsychological assessment was conducted after 6weeks of abstinence. The amount of previous medical detoxifications (F (1, 87) = 4.108, P = .046) and the group of medical detoxifications (F(1, 87) = 4734, P = .032), predicted performance on one out of 14 dependent variables, i.e. the "d2 Number of Signs" task. Though "Age of onset of daily alcohol use" contributed significantly to this relationship, the change of the regression coefficient of the model was ˂10%. The number of non-medical or total amount of previous detoxifications did not predict any of the dependent variables. The results indicate limited evidence of a linear association between either medical, non-medical, or total amount of previous detoxifications and measures of intelligence, speed, attention, or executive functioning, while controlling for relevant confounders.

Experimental Analysis of Long-Term Fuel Trim Performance in a Gasoline Engine Under Various Operating Conditions

This paper analyzes the effect of operating conditions on the enrichment of the fuel-air mixture in a car engine due to a decrease in air mass with increasing altitude above sea level. This study focuses on fuel trim, particularly long-term fuel trim, in optimizing the composition of the fuel-air mixture before it enters the engine's combustion chamber. Experimental studies were conducted on the Bishkek–Osh highway in the Kyrgyz Republic, a road characterized by flat, mountainous, and high-altitude sections with complex terrain. Based on the research objectives, experimental results were obtained, and graphs of long-term fuel trim as a percentage of terrain altitude were constructed and analyzed for flat, mountainous, and high-altitude sections of the Bishkek–Osh highway. The study established that fuel trim indicators can be used to analyze changes in the air-fuel mixture's air excess coefficient (λ = 1, stoichiometric ratio). The reduction in long-term fuel trim was observed in flat, mountainous, and high-altitude sections as air density and pressure decreased with increasing altitude above sea level. The results show that with a reduction in long-term fuel trim to -6.25% to -7.81% at altitudes between 1500 and 3000 meters above sea level, the air excess coefficient (λ) drops to 0.92–0.94. At an altitude of 770 meters (flat terrain), λ was measured at 0.97. The difference in λ (0.03–0.05) indicates that an increase in altitude significantly affects the air-fuel ratio (AFR), impacting mixture formation during vehicle operation in mountainous and high-altitude conditions.

On the sign changes of Dirichlet coefficients of triple product L-functions

On the sign changes of Dirichlet coefficients of triple product <i>L</i>-functions

Microstructure, mechanical properties and high-temperature sliding wear response of a new Al0.5CrFeNiV0.5 high-entropy alloy

In this study, a new V-containing high-entropy alloy (HEA) with the chemical composition of Al0.5CrFeNiV0.5 has been developed. Its microstructural features and phase constitutions were investigated by several techniques, including X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. The as-cast Al0.5CrFeNiV0.5 HEA exhibits an average Vickers hardness of around 570.5 HV, a compressive strength of about 2.53 GPa and a plasticity of around 22.1 %. In addition, the HEA still exhibits very high compressive strength of about 1218.6 MPa at 600 °C, but it decreases quickly to around 586 MPa at 700 °C and 301 MPa at 800 °C. On the other hand, high-temperature sliding wear tests of as-cast HEA against the Si3N4 ceramic balls revealed a slight change of friction coefficient in a range of 0.4–0.5 between RT and 800 °C. However, the wear rate of HEA was found to increase monotonically with increasing the temperature, and was particularly higher when temperature exceeded 600 °C. The associated mechanisms have been discussed in details based on chemical composition analysis, worn surface morphology observations as well as the characterizations of the wear track cross-sections.

Operational control of concrete frost resistance

The analysis of some methods for determining the frost resistance of concrete, including computational and experimental and accelerated ones, has been performed.It is noted that direct methods for determining the frost resistance of concrete are characterized by considerable labor intensity, as well as a long test time, which for concretes of high grades in frost resistance can be several months. Indirect methods do not always make it possible to determine the grade of concrete by frost resistance with a high degree of reliability. The paper proposes an accelerated method for determining the frost resistance of concrete, based on the principles of fracture mechanics, namely the relationship between the frost resistance of concrete and changes in the stress intensity coefficient after a single freeze to a temperature of -50оC. The proposed method allows for operational control of concrete produced monolithic and prefabricated structures. It is shown that the provisions of fracture mechanics describing the process of fatigue failure can be used to describe and analyze the mechanism of frost failure.This will make it possible to develop ways to control the process of frost destruction, slow it down and increase the frost resistance of concrete.

Combined ANFIS and numerical methods to reveal the mass transfer mechanism of ultrasound-enhanced extraction of proteins from millet

Millet protein, as a promising plant-based protein substitute source, is an excellent basis for essential amino acids compared to commonly consumed staple grains. Compared with the traditional extraction process, ultrasound has been used to enhance the extraction efficiency of various plant-based proteins. To reveal the mechanism of ultrasound-enhanced extraction of proteins, adaptive neuro-fuzzy inference system (ANFIS) algorithm and numerical simulation based on Fick’s law were applied to illustrate the mass transfer behavior of millet proteins under different ultrasonic conditions including solid–liquid ratios (S/L ratios), pH and acoustic energy density levels (AED). The results showed that AED dominated the changes in effective diffusion coefficient (De), showing a positive correlation relationship (p < 0.05). Specifically, when the AED was 47.07 W/cm2, the De value increased by 95% compared to that of 23.47 W/cm2. Meanwhile, the ANFIS model successfully predicted protein yields across all investigated parameters, achieving a coefficient of determination (R2) greater than 0.97. This model also elucidated the interactions among four critical factors, among which pH and S/L ratios were the main factors affecting protein yield. Concerning the ultrasonic cavitation bubble dynamics, the bubble collapse efficiency enhanced with an increase in AED, and therefore high AED ultrasound can significantly enhance the cavitation effect. Additionally, the results of the yields and physical properties of millet protein also indicated that in contrast with the traditional extraction methods, the ultrasound impactfully improved extraction yield (by 165%), and combined with pH condition, it decreased the protein particle size (from 813.55 nm to 299.30 nm) without altering the molecular weight distribution. This study offers a novel perspective on the mechanism underlying ultrasound-enhanced protein extraction, drawing upon principles of ultrasonics and extraction processes. The insights gained can serve as a foundation for the food industry to upscale the extraction process, potentially enhancing efficiency and yield.

ESTIMATION OF THE CLEANING TIME OF THE BOTTOM-HOLE ZONE OF WELLS IN CONDITIONS OF UNCERTAINTY

The aim of the work is to analyze changes in the maximum optimal flow rates of wells operating various groups of productive formations of the Volga-Ural oil and gas province under conditions of uncertainty of geological and field data. The relevance of the work is due to the deterioration of the structure of residual oil reserves and the need for the most efficient extraction of liquid hydrocarbon resources, optimization of design methods for various treatments of the bottomhole formation zone. Using geological and statistical modeling systems, the timing of cleaning the bottomhole zones of wells from drilling products was determined at the time they reached their maximum optimal flow rate in conditions of deposits confined to various stratigraphic horizons, and appropriate models of changes in productivity coefficients were constructed. The factors influencing the recovery time of the real properties of the reservoir at the point of opening it by the well, which, among other things, determines the profitability of the process of selecting residual oil reserves, have been established. Among them, the most relevant and necessary for the implementation of an integrated approach to computer support procedures for the development of oil fields are the productivity of wells, fracturing of formations, their proximity to a particular tectonic-stratigraphic complex, geological, physical and physico-chemical properties of formations and their saturating fluids. For the deposits of the Famensk tier of deposits of the Volga-Ural oil and gas province, a multiple decrease in the time of removal of reaction products after hydrochloric acid exposure at objects with low fracturing has been established. At the same time, additional processing of the bottomhole formation zone within areas with high drilling density does not affect the total cleaning time of the bottomhole zone of wells. Stimulation of the removal of drilling mud filtrate and additional products of formation reactions by injection of hydrochloric acid compositions under certain conditions can lead to a decrease in the actual productivity of wells due to the introduction of less developed and dead-end cracks into the drainage process. The existence of the specifics of the procedure for cleaning the bottomhole formation zone depending on the geological and physical parameters of productive formations is substantiated and various patterns of changes in the productivity coefficient depending on the time of wells reaching the maximum optimal flow rate are revealed. The results obtained make it possible to make informed technological decisions to improve the efficiency of oil production, including in conditions of uncertainty, which may be caused by the lack of the necessary volume of hydrodynamic studies of wells.

Numerical Investigation of Large Vehicle Aerodynamics Under the Influence of Crosswind

This paper presents a numerical analysis aimed at estimating the impact of crosswinds on the aerodynamics of large vehicles using ANSYS Fluid Flow and Static Structural, offering insights into the qualitative behaviour of trucks under typical traffic conditions. The cases analysed focus on airflow distribution when a truck, traveling at approximately 100 km/h, passes under a portal while exposed to varying crosswind intensities: weak, moderate, and strong lateral winds. A detailed examination of the truck and portal reveals significant interactions between the induced airflow patterns, affecting truck handling and stability. This is evidenced by shifts in velocity and pressure distributions, changes in drag coefficients, and variations in turbulent kinetic energy, all of which are analysed and discussed in this study.

Conformational Control of σ-Interference Effects in the Conductance of Permethylated Oligosilanes.

As silicon-based integrated circuits continue to shrink, their molecular characteristics become more pronounced. However, the structure-property relationship of silicon-based molecular junctions remains to be elucidated. Here, an intuitive explanation of the effects of backbone dihedral angles on transport properties in permethylated oligosilanes is presented employing the Ladder C model Hamiltonian combined with nonequilibrium Green's function formalism. Backbone dihedral angles modulate quantum interference (QI), resulting in the change of the transmission coefficient at the Fermi energy (EF) by up to 6 orders of magnitude in Si4Me10. Because the types of QI (constructive or destructive) between molecular conductance orbitals (MCOs) are unchanged, the relative magnitudes of contributions from QI are critical. This quantitative aspect of QI is often neglected in previous theoretical studies. Small backbone dihedral angles lead to localized MCOs near EF and delocalized MCOs further away from EF. As a result, the constructive QI between the MCOs near EF is suppressed, while the destructive QI between other MCOs is enhanced. This insight opens an avenue to harness QI to realize ultrainsulating molecular devices.

Reliability Analysis of Transmission Tower Based on Unscented Transformation Under Ice and Wind Loads

Due to the complexity of the transmission tower structure and the correlation between wind and ice loads in the actual project, it is difficult to analyze the reliability of transmission towers with traditional methods. To solve this problem, the unscented transformation (UT) principle is presented concisely and used in the reliability analysis of transmission towers in this paper. Moreover, the finite element model of the target transmission tower is created. The reliability indices of the transmission tower under various loading cases are evaluated using UT and analyzed relative to the outcomes of the Monte Carlo method (MCS). Lastly, by analyzing and validating a wine-cup shape tangent tower, the simulation results show that the UT yields reliability indices with less than 6% relative error compared with MCS results for the transmission towers with lower reliability, which are more important in engineering. Variations in error caused by the change in correlation coefficients among variables are small. Consequently, the efficiency of calculations is improved by the UT-based reliability calculations for transmission towers in the case of correlated variables, which better meet engineering application requirements. It is proved that the method of reliability analysis for transmission towers based on the UT is applicable.

Research on Emission Reduction Decisions in Supply Chains Considering Vertical Spillover Effects and Low-Carbon Preferences

The growth in carbon emissions is increasingly exacerbating global warming. As the principal source of carbon emissions, companies can effectively enhance their emission reduction levels through the vertical spillover of emission reduction technologies to investigate the impact of vertical spillover rates, consumers’ low-carbon preference coefficients, emission reduction cost coefficients on optimal supply chain decisions, and profits in centralized and decentralized decision-making environments. Considering consumers’ preferences for low-carbon options, this paper constructs a Stackelberg game model under centralized and decentralized supply chain decision-making scenarios. It examines the effects of considering the vertical spillover effects of emission reduction versus not taking them into account. Using backward induction, this study optimizes the emission reduction levels of leading suppliers and manufacturers. The results indicate that an increase in consumers’ low-carbon preference levels and vertical spillover rate not only enhances the emission reduction levels of suppliers and manufacturers but also increases their profits. Conversely, an increase in emission reduction cost coefficients impedes emission reductions, with a more pronounced effect under vertical spillover conditions. In centralized decision-making, increases in vertical spillover rates, consumers’ low-carbon preferences, and decreases in emission reduction cost coefficients create a synergistic effect, resulting in greater increases in emission reduction levels and profits for suppliers and manufacturers compared to the sum of the effects of changes in individual coefficients. This finding provides new insights for governments in formulating relevant policies to promote corporate emission reductions.