Load Factor Research Articles

Quantifying the impact of subgrade stiffness on the railway dynamic load factor using instrumented wheelset and MRail measurements

Quantifying the impact of subgrade stiffness on the railway dynamic load factor using instrumented wheelset and MRail measurements

Any way the wind blows: quantifying superbubbles and their outflows in simulated galaxies across z ≈ 0 − 3

Abstract We present an investigation of clustered stellar feedback in the form of superbubbles identified within eleven galaxies from the FIRE-2 (Feedback in Realistic Environments) cosmological zoom-in simulation suite, at both cosmic noon (1 < z < 3) and in the local Universe. We study the spatially-resolved multiphase outflows that these supernovae drive, comparing our findings with recent theory and observations. These simulations consist of five LMC-mass galaxies and six Milky Way-mass progenitors (with a minimum baryonic particle mass of mb.min = 7, 100M⊙). For all galaxies, we calculate the local and galaxy-averaged mass and energy loading factors from the identified outflows. We also characterize the multiphase morphology and properties of the identified superbubbles, including the ‘shell’ of cool (T < 105 K) gas and break out of energetic hot (T > 105 K) gas when the shell bursts. We find that these simulations, regardless of redshift, have mass-loading factors and momentum fluxes in the cool gas that largely agree with recent observations. Lastly, we also investigate how methodological choices in measuring outflows can affect loading factors for galactic winds.

Safety of Oral Food Challenges for Individuals with Low Levels of Cow's Milk-Specific Immunoglobulin E Antibodies.

Cow's milk (CM) is one of the most common food allergens in Japan. The oral food challenge (OFC) of CM is important for the definite diagnosis of children with CM allergy and it is recommended to be actively and safely performed in individuals with low CM-sIgE levels. This study aimed to investigate the safety of low-dose CM-OFC in individuals with low CM-sIgE levels and discuss the prognostic factors and appropriate approaches for assessing the starting doses of CM-OFC in these individuals. We retrospectively analyzed 6,929 OFC tests conducted between January 1, 2017 and December 31, 2021; of which, 1,390 were CM-OFC tests. The characteristics, OFC-positive rates, CM loading, and related factors were analyzed in 138 cases involving low CM-sIgE levels. Stepwise OFC tests were conducted according to the FA guidelines in Japan using an open and unblinded method. Among 138 individuals with low CM-sIgE levels, 110 (79.7%) passed the OFC test without any symptoms. Among the cases with OFC-positive status, 50.0% (14/28) cases showed symptoms with low-dose OFC (30-105 mg CM protein). Moreover, complete CM elimination was associated with a significantly high OFC-positive rate, and 60.0% (12/20) of the cases involving complete CM elimination showed symptoms with low-dose OFC. Eighty percent of the patients with low CM-sIgE levels safely completed the OFC test. Nevertheless, careful observation is essential during low-dose OFC test in cases with low CM-sIgE levels, especially in the cases with complete elimination. The starting dose of the OFC test should be re-evaluated and modified using baked milk or a lower dose of CM to ensure safety and early outgrowth of CM allergy.

Multi-Objective Optimization Algorithm Based Bidirectional Long Short Term Memory Network Model for Optimum Sizing of Distributed Generators and Shunt Capacitors for Distribution Systems

In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution systems at any desired load factor. The stochastic traits of evolutionary computing methods necessitate running the algorithm repeatedly to confirm the global optimum. In order to save utility engineers time and effort, this study introduces a BiLSTM network-based machine learning model to directly estimate the optimal values of DGs and SHCs, rather than relying on load flow estimates. At first, a multi-objective grey wolf optimizer determines the most suitable locations and capacities of DGs and SHCs at the unity load factor and the same locations are used to obtain optimum sizing of DGs and SHCs at other load factors also. The base case data sets consisting of substation apparent power, real power load, reactive power load, real power loss, reactive power loss and minimum node voltage at various load factors in per unit values are taken as input training data for the machine learning model. The optimal sizes of the DGs and SHCs for the corresponding load factors obtained using GWO algorithm are taken as target data sets in per unit values for the machine learning model. An adaptive moment estimation (adam) optimization approach is employed to train the BiLSTM ML model for identifying the ideal values of distributed generations and shunt capacitors at different load factors. The efficacy of the proposed ML-based sizing algorithm is demonstrated via simulation studies.

Development of the Indonesian sexual quality of life scale for women (ISQOL-W)

Sexual quality of life is greatly influenced by sexual function, yet thorough measures remain limited and vary across regions. In Indonesia, diverse cultural and religious contexts notably shape sexual quality of life. Thus, it is important to have a tool that considers both internal and external aspects. The aim of this study was to develop a valid and reliable scale that specifically measures Indonesian sexual quality of life for women (ISQOL-W), considering cultural and social factors. A total of 228 participants were recruited from April 30, 2023, to September 30, 2023. The ISQOL-W was developed through two phases: item generation and psychometric evaluation. In the first phase, 68 items were drafted based on definitions and dimensions of sexual quality of life. In the second phase, exploratory factor analysis resulted in 34 items with a loading factor greater than 0.4 (ranging from 0.41 to 0.84) which were categorized into four domains/factors: sexual-related emotion, sexual fantasy, sexual arousal, and sexual relationship. The Cronbach’s α coefficient for the overall questionnaire was 0.915, with subscale reliability ranging from 0.826 to 0.903. Further analysis revealed significant differences in ISQOL-W scores across relationship status, educational level, history of last sexual activity, and type of sexual activity. In conclusion, the ISQOL-W demonstrated robust psychometric properties, supporting its use in future studies. This study represents the first effort to develop and validate a sexual quality of life scale specifically for Indonesian women.

Optimal Location Identification of Solar PV Systems in Distributed Generators Based on Prediction of Load Flow and Factor Using Rule Based Deep Learning Algorithm

Optimal Location Identification of Solar PV Systems in Distributed Generators Based on Prediction of Load Flow and Factor Using Rule Based Deep Learning Algorithm

Allowable stress rating compared to load and resistance factor rating for timber bridges with and without steel-beam retrofit

This paper presents the relevancy of the Allowable Stress Rating (ASR) and the Load and Resistance Factor Rating (LRFR) methods for timber bridges. Benchmark bridges constructed in the 1930′s are upgraded with hollow structural steel (HSS) beams and three-dimensional finite element models provide technical information that is necessary for examining their behavior and rating evaluations. Complying with published manuals, a total of 17 rating vehicles are considered across three categories (Design, Legal, and Permit) so as to generate the maximum responses of the bridges. The position of the vehicles dominates the deflection profiles of the unrepaired bridges. After installing the HSS beams, the live loads are redistributed and stiffness enhancement is noticed in the transverse direction of the bridges. The rating factors calculated with ASR exceed those with LRFR for the unrepaired bridges, regardless of vehicle configurations, and the level of disparity between these rating approaches increases when the bridges are repaired owing to differences in load factors. In terms of sensitivity to average daily truck traffic, the LRFR factors of the bridges under the Legal vehicles are more responsive than the factors subjected to other vehicle types. From a probability perspective, the compatibility of these rating methodologies varies contingent upon vehicle categories and the presence of the HSS beams. Practice guidelines are proposed to facilitate the conversion of rating factors between ASR and LRFR as a function of the present condition of constructed timber bridges.

Lithography-Based Metal Manufacturing of Copper: Influence of Exposure Parameters on Green Part Strength

Copper’s high thermal and electrical conductivity enables its application in heat exchangers and high-frequency components. For those applications, additive manufacturing has advantages with respect to functional integration, miniaturization, and reduced waste. However, the processing of copper is a challenge for established laser-based processes since copper’s high reflectivity impedes energy input. Sinter-based additive manufacturing processes do not exhibit this limitation since the energy for the fusion of material is applied by thermal energy during sintering. This makes them an ideal candidate for copper manufacturing. In the following work, Lithography-based Metal Manufacturing (LMM) of copper is demonstrated. Curing behavior is investigated by single-layer exposure (SLE) tests measuring curing thickness for different loading factors, particle sizes, and exposure times. Bending strength is investigated as a function of exposure time, loading factor, and orientation in the building space. A higher exposure time and lower loading factors increase bending strength. Furthermore, samples with different loading factors are produced to measure the impact of the loading factor on sintered density. For these parameters, no clear trend is demonstrated.

Assessing the Carbon Intensity of e-fuels Production in European Countries: A Temporal Analysis

The transport sector heavily relies on the use of fossil fuels, which are causing major environmental concerns. Solutions relying on the direct or indirect use of electricity through e-fuel production are emerging to power the transport sector. To ensure environmental benefits are achieved over this transition, an accurate estimation of the impact of the use of electricity is needed. This requires a high temporal resolution to capture the high variability of electricity. This paper presents a previously unseen temporal analysis of the carbon intensity of e-fuels using grid electricity in countries that are members of the European Network of Transmission System Operators (ENTSO-E). It also provides an estimation of the potential load factor for producing low-carbon e-fuels according to the European Union legislative framework. This was achieved by building on top of the existing EcoDynElec tool to develop EcoDynElec_xr, a python tool enabling—with an hourly time resolution—the calculation, visualisation, and analysis of the historical time-series of electricity mixing from the ENTSO-E. The results highlight that, in 2023, very few European countries were reaching low carbon intensity for electricity that enables the use of grid electricity for the production of green electrolytic hydrogen. The methodological assumptions consider the consumption of the electricity mix instead of the production mix, and the considered time step is of paramount importance and drastically impacts the potential load factor of green hydrogen production. The developed tools are released under an open-source license to ensure transparency, result reproducibility, and reuse regarding newer data for other territories or for other purposes.

Hospital Customer Competition Issues are being addressed through Confirmation Factor Analysis on Experiential Marketing, Brand Trust, and Loyalty

Introduction The post-COVID-19 pandemic has caused an epidemiological transition that has pushed the pace of development of the health service system even further. Issues and revolutions in the health service industry have made all health service industry providers compete with each other to get service users with competitive advantages in the potential global health market. The hospital has improved revenue sustainability while promoting quality assurance practices. These healthcare industry managers have become adept at introducing business practices into business operations to increase the market for hospital customers. Exploratory factor analysis on important marketing dimensions such as experiential marketing, brand trust, and patient loyalty is very much needed in the issue of competition in the health service industry in hospitals. Materials and Methods This research was quantitative research with a survey approach to outpatients with a sample size of n=255 patients according to Lemeshow (1997). Identification of loading factor analysis includes experiential marketing variables, brand trust, and loyalty. Data analysis used IBM SPSS Statistics 26 Results The research results showed 1) an important loading factor on the experiential marketing variable is the Think dimension indicator (0.845), 2) an important loading factor on the brand trust variable is the brand characteristic dimension (0.945) and 3) an important loading factor on variable loyalty is Repeat Purchase (0.925) Conclusion Dimension of brand trust is the most important dimension in the issue of competition in the health service industry in hospitals. Strengthening and expanding hospital branding as a promotion strategy to add positive value to the reputation of patient and community services at the hospital.

GA-NIFS: JWST/NIRSpec IFS view of the z ∼ 3.5 galaxy GS5001 and its close environment at the core of a large-scale overdensity

We present JWST Near-Infrared Spectrograph (NIRSpec) observations in integral field spectroscopic (IFS) mode of the galaxy GS5001 at redshift z = 3.47, the central member of a candidate protocluster in the GOODS-S field. The data cover a field of view (FoV) of 4″ × 4″ (∼30 × 30 kpc2) and were obtained as part of the Galaxy Assembly with NIRSpec IFS (GA-NIFS) GTO programme. The observations include both high (R ∼ 2700) and low (R ∼ 100) spectral resolution data, spanning the rest-frame wavelength ranges 3700–6780 Å and 1300–11850 Å, respectively. These observations enable the detection and mapping of the main optical emission lines from [O II]λλ3726, 29 to [S III]λ9531. We analysed the spatially resolved ionised gas kinematics and interstellar medium properties, including obscuration, gas metallicity, excitation, ionisation parameter, and electron density. In addition to the main galaxy (GS5001), the NIRSpec FoV covers a close companion in the south, with three sub-structures with velocities blueshifted by ∼ − 150 km s−1 with respect to GS5001, and another source in the north redshifted by ∼200 km s−1. Optical line ratio diagnostics indicate star formation ionisation and electron densities of ∼500 cm−3 across all sources in the FoV. The gas-phase metallicity in the main galaxy is 12+log(O/H) = 8.45 ± 0.04, and slightly lower in the companions (12+log(O/H) = 8.34 − 8.42), consistent with the mass-metallicity relation at z ∼ 3. We find peculiar line ratios (high log[N II]/Hα = [−0.45, −0.3], low log[O III]/Hβ = [0.06, 0.10]) in the northern part of GS5001. These could be attributed to either higher metallicity, or to shocks resulting from the interaction of the main galaxy with the northern source. We identify a spatially resolved outflow in the main galaxy, traced by a broad symmetric component in Hα and [O III], with an extension of about 3 kpc. We find maximum outflow velocities of ∼400 km s−1, an outflow mass of (1.7 ± 0.4)×108 M⊙, a mass outflow rate of 23 ± 5 M⊙ yr−1, and a mass loading factor of 0.23. These properties are compatible with star formation being the driver of the outflow. Our analysis of these JWST NIRSpec IFS data therefore provides valuable, unprecedented insights into the interplay between star formation, galactic outflows, and interactions in the core of a z ∼ 3.5 candidate protocluster.

Reactive Extraction of Carboxylic Acids (Lactic, Propionic and Succinic Acids) using Tri-n-Butyl Amine Dissolved in Various Diluents

The current study intends to look into the extraction of lactic acid, propionic acid and succinic acids from aqueous solutions of these substances utilizing various solvent-extractant combinations to ascertain the most effective composition for the reactive extraction. The commercial value of succinic, propionic, and lactic acids in industrial processes led to their selection as the carboxylic acids. The process of recovering carboxylic acids from their aqueous solutions is accomplished by the Process Intensification method of reactive Tri-n-Butyl Amine was employed in the experiments because it has better stability, a lower water solubility, and is more eco-friendly than other extractants of the amine type. The extractants were dissolved in various diluents with various chemical structures, including 1-octanol, chloroform, and dimethylene chloride. Each experiment was conducted at 298.15 K. The distribution coefficient (KD), loading factor (Z), and extraction yield (%E) were used to compare the results in the range of 0.1 to 0.4 N acid concentration at various concentrations of Tri-n-Butyl Amine (10% to 40%). It was observed that at 0.1N and 40% amine concentration succinic acid attains a maximum distribution coefficient KD is 8.01 and equilibrium complexion KE1 is 7.5 for Tri-n-Butyl Amine, followed by propionic acid and lactic acid and a (1:1) type of acid amine complex was observed. The kinetic studies that were carried out using stirred cells to figure out the kinetic parameters such as order of the reaction with respect to acid and amine, mass transfer coefficient, and rate constant are also reported. The reaction with the highest Hatta number, MH=14, occurs in an instantaneous regime in 1-octanol when succinic acid and Tri-n-Butyl Amine interact.

Evaporator Evaluation as a Heat Exchanger in Refrigeration Systems at Constant Thermal Load and Fouling Factor

Heat exchangers are widely used in various industrial installations, one of which is their use in air conditioning systems. In the design process of heat exchangers, the main focus is to determine the dimensions of the device. This is done to determine the performance of the heat exchanger, where the calculation is based on a constant thermal load and a constant fouling factor. When the heat exchanger is first operated, the mass flow rate of the cooling fluid must be lower than the design point to maintain a constant cooling load. However, the conditions for the formation of deposits on the surface of the heat exchanger cannot be known. Therefore, designing a heat exchanger with a constant fouling factor is less realistic.

Oxidative degradation of chitosan by Fe-MCM-41 heterogeneous Fenton-like system

We herein disclosed an efficient multiphase Fenton-like catalytic system for oxidative degradation of chitosan. By utilizing Fe-MCM-41, featured with regular mesoporous structure and high specific surface area, the activation efficiency of H2O2 was significantly enhanced and the chitosan degradation efficiency proved by 28.1% higher than the conventional system using H2O2 alone. Under optimized conditions (5 g/L chitosan, 0.5 g/L Fe-MCM-41, 0.16 mol/L CH3COOH, 0.86 mol/L H2O2, 50 °C, 140 min), the viscosity reduction rate of chitosan reached an impressive 98.2%. Among the catalysts tested, Fe-MCM-41 with a loading factor of x = 0.12 demonstrated optimal degradation performance. After four recycles, the degradation efficiency maintained > 93.6%, demonstrating its excellent stability and recyclability for potential industrial applications. Kinetic studies provided further elucidation of the reaction mechanism, which indicated that the degradation process of chitosan followed a first-order kinetic model, with an apparent activation energy (Ea) of 48.91 kJ/mol. This novel and efficient strategy for chitosan degradation, addressed the challenges of catalyst recovery and secondary pollution typically associated with traditional Fenton systems, and posed broad application potential for polysaccharide material processing.

Feedback-regulated seed black hole growth in star-forming molecular clouds and galactic nuclei

Context. The detection of supermassive black holes (SMBHs) in high-redshift luminous quasars may require a phase of rapid accretion, and as a precondition, substantial gas influx toward seed black holes (BHs) from kiloparsec or parsec scales. Our previous research demonstrated the plausibility of such gas supply for BH seeds within star-forming giant molecular clouds (GMCs) with high surface density (∼104 M⊙ pc−2), facilitating “hyper-Eddington” accretion via efficient feeding by dense clumps, which are driven by turbulence and stellar feedback. Aims. This article presents an investigation of the impacts of feedback from accreting BHs on this process, including radiation, mechanical jets, and highly relativistic cosmic rays. Methods. We ran a suite of numerical simulations to explore diverse parameter spaces of BH feedback, including the subgrid accretion model, feedback energy efficiency, mass loading factor, and initial metallicity. Results. Using radiative feedback models inferred from the slim disk, we find that hyper-Eddington accretion is still achievable, yielding BH bolometric luminosities of as high as 1041 − 1044 erg/s, depending on the GMC properties and specific feedback model assumed. We find that the maximum possible mass growth of seed BHs (ΔMmax BH) is regulated by the momentum-deposition rate from BH feedback, ṗfeedback/(ṀBHc), which leads to an analytic scaling that agrees well with simulations. This scenario predicts the rapid formation of ∼104 M⊙ intermediate-massive BHs (IMBHs) from stellar-mass BHs within ∼1 Myr. Furthermore, we examine the impacts of subgrid accretion models and how BH feedback may influence star formation within these cloud complexes.

Crack Propagation Tests for Load Sequences Developed Using Different Flight Parameters of a Trainer Aircraft

Abstract Military aircraft are subjected to highly variable and unpredictable loads due to diverse mission profiles, armament configurations, and individual piloting styles. This variability complicates the definition of precise load spectra, particularly in cases where data loss occurs due to Flight Data Recorder (FDR) malfunctions or data mishandling. This paper investigates the use of different flight parameters, such as load factor (nz ), barometric height (Hb ), and horizontal velocity (Vp ), to define load sequences for the PZL-130 “Orlik” TC-II military trainer aircraft. These sequences were then used to evaluate crack propagation using Compact Tension (CT) specimens. The results show that the incorporation of additional flight parameters improves the accuracy of crack propagation predictions when compared to direct strain measurements. This study highlights the potential of using available flight data to develop reliable load spectra for fatigue life estimation in military aircraft, even when direct load measurements are not financially feasible.

A Study of Heavy Road Freight Transport in Poland in the Context of the Pursuit of Sustainable Road Transport

The efficiency of road freight transport determines—to a significant degree—the total environmental footprint and the amount of greenhouse gases and other pollutants released into the atmosphere by inland transport. The rate of empty or partially empty vehicles is one of the key metrics for improvement of the environmental performance of freight road transportation. This paper presents the characteristics of road freight transport in Poland on the basis of data collected by weigh-in-motion stations. Data aggregation for environmental analysis represents a novel aspect of the work. Indicators describing the degree of loading, the share of empty vehicles in traffic, and the share of vehicles of maximum permissible total weight in traffic were determined for a representative group of heavy goods vehicles. Based on the representative load factor value (LFA), a classification of the road section into four groups was proposed. The results obtained show a clear differentiation of the values of the indicators analyzed for individual groups and their variability in the three-year period covered by the analysis. The aggregation method presented can be used to identify the nature of the distribution of the weight categories of the heavy goods vehicles and provide input information for targeted analyses relating to sustainable road transport management and environmental protection. Finally, the grouped LFA values were linked with indicators of energy consumption (ECI) and on-road emissions (EI).

Construct Analysis of AMDA Model Syntax Using the Structural Equation Modeling-Partial Least Square (SEM-PLS) Method

When a building is damaged by an earthquake, it's essential to assess its safety. The AMDA model is the result of the stages of developing a competency-based training model for Post-Earthquake Building Investigation which is designed to make someone competent in this matter. The construct of a development model needs to be tested for validity, reliability and evaluation of the construct or structural model of the syntax of the model being built. Each syntax is confirmed or tested through the value of loadings factor, Average Variance Extracted (AVE) and composite reliability. Next, the influence between variables is analyzed or the structural model or construct (Inner Model) is evaluated. Construct evaluation can be seen from the value of R2 (R-square) between 0 and 1 (0<R2<1), the greater the value and closer to 1, the greater the influence of syntax on the model. The test was carried out using the Structural Equation Modeling-Partial Least Square (SEM-PLS) method. The results obtained were loading factor values>0.7, meaning the indicators used in the syntax were valid, AVE>0.5 meaning the syntax was valid, composite reliability value>0, 7 means the syntax is reliable and the value of R2=0.963, a significant influence of the syntax on the model

Development of a magnetic rotator to enhance the hydrogen evolution reaction in a proton exchange membrane water electrolysis cell

In this study, a large-scale magnetic rotator for hydrogen production boosting was designed. The study addresses the challenge of selecting and designing mechanical components for a dynamic magnetic field (DMF) magnetic rotator in a green hydrogen electrolysis power plant, focusing on ensuring component reliability and efficiency under operational stresses. The aim is to determine suitable machine element materials (shaft, clutch, gears, etc.), allowable shear stress, and interconnection mechanisms through theoretical and practical evaluations. The method includes calculating the allowable shear stress for the spline based on carbon steel tensile strength, applying safety factors for material properties and load considerations, and determining shaft diameter using torque and shock load factors. Standard catalogs guide the selection of interconnections like clutches, gears, and bearings to ensure compatibility and performance. The results indicate that a 95 mm diameter S30C carbon steel shaft, with an allowable shear stress of 7.8 kg/mm2, meets the design requirements. The chosen spline dimensions and a 12.5 MW, 14-pole induction motor align with the system’s needs, ensuring reliable operation. The discussion highlights the critical balance between theoretical predictions and practical application in design optimization. It underscores the importance of incorporating safety factors and verifying component suitability to ensure robust performance of the magnetic rotator. This study provides a comprehensive approach to design optimization, integrating theoretical analysis with practical considerations to achieve optimal performance and reliability. The design output of this study can be used to boost the hydrogen evolution reaction in the SIEMENS Sylizer 300 electrolysis cell.

Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin

This research used the improved export coefficient model to estimate non-point source load in sub-watersheds and a self-organizing map model to identify the correlation relationship of factors, that can be affected by non-point source load in Yangtze River Basin. Research results indicate that total nitrogen load is 4.87 - 15.53 kg/ha; total phosphorus load is 0.18 - 0.51 kg/ha; Dong Ting Lake sub-basin has the lowest contribution value of total nitrogen and phosphorus; Tai Lake sub-basin has the highest contribution load of total nitrogen and total phosphorus; Jinsha River sub-basin reveals the highest value of total nitrogen and phosphorus contribution on grassy land and desert land; Tai Lake sub-basin has the highest total nitrogen and total phosphorus load on forest, agricultural land, and urban construction land. The correlation relationship of factors reveals a very close correlation with each other as precipitation, total nitrogen load, and total phosphorus load factors have correlation in the highest value, in which total nitrogen load and total phosphorus load factors have a close correlation with each other from the lowest value to highest value; wetland and barren land factors correlate with the lowest value and the highest value; agricultural land, forestland, and grassy land factors correlate with one another in the high value and the highest value. The forest cover rate factor, as well as the population factor, does not correlate with other factors.