Load Factor Research Articles

Energy Flexibility Strategies for Buildings in Hot Climates: A Case Study for Dubai

This paper presents a case study of energy flexibility strategies for a building located in the hot climate of Dubai, a type of climate in which energy flexibility has been under-researched. Energy flexibility is changing the routine-consumption profile and deviating from the normal operation of the building by the users to manage the variability in the load profile and cost of electricity. The three flexibility strategies being considered are based on the modulation of the indoor air temperature setpoint profile while considering different marginal costs for electricity. The main objective is to quantify the energy storage flexibility of each strategy and evaluate its impact on the system ramping and load factor. The study was carried out utilizing a grey-box, resistance–capacitance model of the building, which was validated against experimental measurements. This study is the first to use the following five indicators simultaneously: load factor, system ramping, storage capacity, peak-period demand reduction, and cost savings. Combining these indicators helps building facility managers and distribution system operators (DSOs) better understand the implications of implementing a specific flexibility strategy in a building or a group of buildings. When comparing the indicators of each strategy with each other, it was observed that depending on the amplitude of the change in the electricity cost signal during the peak period, a significant cost reduction of more than 25% could be achieved through the implementation of specific flexibility strategies compared with the normal baseline operating condition.

Method of calculation of temperature parameters and servic life of cable lines with a voltage of 10 kV

RELEVANCE. The paper presents a method for calculating the temperature parameters and service life of cable lines (CL) with a voltage of 10 kV for various types of insulation and operating conditions. Dependencies have been developed that are recommended for clarifying the parameters of the CL, taking into account different operating modes. The results of the study can be used for practical application and will contribute to reducing the number of accidents resulting from thermal breakdowns of CL due to incorrect selection of CL parameters.PURPOSE. To investigate the temperature parameters of 10 kV CL, taking into account various methods of laying them and load factors for the climatic conditions of the Republic of Tatarstan.METHODS. Methods for calculating the temperature parameters of CL and their service life, methods of statistical data processing, and methods for approximating functions are used. The ELCUT software package is used to visualize the results obtained during calculations. results. The results of calculations of the temperature parameters of 10 kV CL with paper-impregnated insulation (BPI), polyvinyl chloride plastic (PVC) insulation and polyethylene (PE) insulation during their laying in air, in the ground, in the ground in a pipe, taking into account the load coefficients of cable lines, are presented. The results of calculations of the service life of the CL are shown. The values of the optimal load coefficients of the CL are determined to reduce the rate of thermal aging of insulation under various operating conditions. conclusion. The results of the conducted research and calculations can be used to evaluate and select the optimal load of 10 kV CL at the stages of operation and design of power supply systems.

Efficient optimization-based method for simultaneous calibration of load and resistance factors considering multiple target reliability indices

This study introduces an innovative optimization process for calibrating probabilistic load and resistance factors (LRFs) in limit state designs, effectively accommodating multiple target reliability indices. Given the impracticality of direct Monte Carlo simulations (MCS) for this task, a response surface method (RSM) is proposed to approximate load and resistance components separately rather than fitting conventional safety factors. This approach eliminates the need for additional implicit evaluations, thereby improving the efficiency of LRF calibration across multiple targets. The process is further enhanced by an adaptive boundary algorithm that updates search domains in real-time, streamlining the optimization. Validation through three examples—including one explicit and two implicit performance functions (a structural and a geotechnical example)—demonstrates that the method achieves accurate results with fewer iterations by dynamically narrowing search domains. Specifically, the accuracy of the proposed method is confirmed by comparing results with those from the literature for the explicit example and with basic MCS results applied to the initial implicit problems. Performance on the illustrative examples shows that the structural example achieves calibration for three targets within ten iterations. Additionally, this method eliminates the need for approximately ten thousand implicit evaluations when calculating limit state points for the geotechnical example.

Optimal lamination angles via exact and efficient differentiation of the geometrically nonlinear finite element solution

Laminates allow tailoring the fiber orientations in the layers to obtain the desired mechanical response. The optimal layup design is a challenging task in the case of finite deformations and buckling. For an assigned design, an incremental-iterative finite element analysis is needed to compute the structural response. Gradient-based methods are very often the most efficient optimization tools. Their bottleneck is the gradient evaluation, generally possible only approximately by finite differences. This article shows how to compute the exact gradient of the geometrically nonlinear finite element solution with respect to the stacking sequence. The strategy relies on the implicit differentiation of the nonlinear discrete equations of a control equilibrium point corresponding to an assigned displacement. This provides the load factor gradient by a single fast-solution linear system with the already factorized tangent stiffness matrix, regardless of the number of design variables, and scalar products involving the partial derivatives of the discrete internal force vector, calculated in an exact and efficient way. Several applications demonstrate the efficiency and robustness of the approach.

A Review of Structural Systems to be Built on Planets

The architectural construction process on planets is an architectural issue that develops day by day due to extreme environmental conditions and uncertainties. Architectural design needs structural systems to survive. Structural systems on planets encounter load factors that are different from the load factors on Earth. Choosing the optimum structural system is important for the structures planned to be built on planets to survive under the effects and loads of the environment and to adapt to human physiology. Some of the different types of structural systems used on Earth are featured in the literature for building a structure on planets. An evaluation system has been created to determine the correct system type for the first settlements on planets among the prominent structural system types and to narrow down the selection area of these system features. In line with this evaluation system in this study, a structural system model that stands up to harsh environmental conditions and protects human health is proposed for the first settlements on the planets. It is aimed that the evaluation system will be developed in the light of research emerging from developing technologies and can be used in future studies.

Inverse Correlation of Th2-Specific Cytokines with Hepatic Egg Burden in S. mansoni-Infected Hamsters.

Schistosomiasis, a parasitic disease caused by Schistosoma spp., affects more than 250 million people worldwide. S. mansoni in particular affects the gastrointestinal tract and, through its eggs, induces a Th2 immune response leading to granuloma formation. The relationship between egg load and immune response is poorly understood. We investigated whether the quantity of parasitic eggs influences the immune response in S. mansoni-infected hamsters. The hepatic and intestinal egg load was assessed, and cytokine expression as well as the expression of three major egg-derived proteins were analyzed in monosex- and bisex-infected animals by qRT-PCR. Statistical correlations between egg load or egg-derived factors Ipse/alpha-1, kappa-5, and omega-1, and the immune response were analyzed in liver and colon tissue. Surprisingly, no correlation of the Th1 cytokines with the hepatic egg load was observed, while the Th2 cytokines Il4, Il5, and Il13 showed an inverse correlation in the liver but not in the colon. A longer embryogenesis of the parasitic eggs in the liver could explain this correlation. This conclusion is supported by the lack of any correlation with immune response in the colon, as the intestinal passage of the eggs is limited to a few days.

Instrument Construction and Exploration of Students' CollaborationSkillsBased on the Summated Rating Scale

One of the essential 21st-century skills that students must possess is the ability tocollaborate. However, profiling students' collaboration skills is challengingwithout valid and reliable instruments. Therefore, this research aims to map the profile of students' collaboration skills using valid and reliable instruments. This study is descriptive-explorative research with a quantitative approach. The research sample included 900 Islamic Senior High School/Madrasah Aliyahstudents, with 150 students participating in the instrument trials and 750 servingas the primary sample in this study. The results indicate that the collaborationability instrument is valid and reliable, as demonstrated by a loading factor value > 0.5, T-Value > 1.96, RMSEA 0.00 < 0.08, RMR 0.043, Std. RMR0.040, GFI 0.95, AGFI 0.87, NNFI 0.97, CFI 0.98, IFI 0.98, RFI 0.97, PNFI 0.85, and a composite reliability coefficient CR=0.909 from the second-order confirmatoryfactor analysis. The findings show that students' collaboration skills are moderate, with an average score of 26.4, which falls within the medium category. The distribution of students' abilities is as follows: 347 students (46.3%) are classifiedas having moderate abilities, 207 students (27.6%) as having high skills, and 196students (26.1%) as having low skills. Based on these results, teachers andstakeholders are encouraged to enhance students' collaboration skills throughstudent-centred learning approaches, such as project-based learning, which canprovide students with opportunities to engage and practice working together actively in the learning process.

Quantifying the impact of rail longitudinal level changes on dynamic load magnitudes through instrumented wheelset measurements

Track geometry significantly influences train-track dynamic interactions, primarily due to irregularities at the wheel-rail interface. These irregularities generate dynamic load excitations, leading to defects and damage. This study evaluates how track surface profile longitudinal level vertical changes affect vertical wheel-to-rail loads, quantified by the dynamic load factor ( ϕ ), due to the importance of ϕ in track design. A limitation of the existing studies is their focus on instrumented sections and numerical modellings without considering different track structures. This study conducted dynamic load measurements using two instrumented wheelsets (IWS) over a 340 km section operated by a North American Class 1 freight railway in the Canadian Prairies under various track structures and train speeds. Rail surface longitudinal level measurements were obtained as routine measurements through a track geometry car. The paper presents statistical distributions of rail longitudinal level across different track structures and evaluates two widely used and recently developed ϕ equations within the context of North American freight railways to quantify the impact of rail longitudinal level (i.e. profile) changes on dynamic load magnitudes. The study also evaluates regulated threshold values by considering observed trends in the measured data, which aims to quantify and compare these values with our current understanding.

Functional whey-based drinks with grape pomace extract and fruit juice

Industrial waste leads to pollution and deterioration of the environment, as well as harming the living population and animals. Whey, being a by-product of milk processing, is a source of protein and nitrogenous compounds, carbohydrates, lipids, mineral supplements, vitamins, organic acids, enzymes and macro- and microelements. Amino acid content of whey is represented by amino acids of protein substances and free amino acids. The next valuable secondary raw material is grape pomace, which is practically not processed and becomes a factor of anthropogenic load, polluting the environment. Grape pomace has a rich chemical composition, especially a large number of phenolic compounds, which have antioxidant properties. Currently, there is a significant increase in the production and consumption of soft drinks with various additives, the composition of which is replete with unnecessary colors and flavors. The aim of the work is to use milk whey for the development of technology of drinks of functional purpose, which will directly increase the efficiency of its processing, as a secondary raw material in industrial production, as well as serve the purpose of improving the environmental situation in places where milk processing plants are located. In particular, the creation of functional drinks on the basis of milk whey with the addition of grape pomace, fruit juices and pectin, will enrich the milk drink with a complex of biologically active substances, trace elements, antioxidants, vitamins. Using organoleptic and physico-chemical parameters, two technologies of functional drinks based on milk whey with 25% Husein Black grape pomace extract, in the first 25% cherry and in the second 25% peach juices were developed. The first formulation demonstrated noteworthy macro- and microelement content, including calcium (12.10%), sodium (5.04%), magnesium (1.60%), phosphorus (7.31%), and potassium (24.61%). Similarly, the second formulation exhibited significant macro- and microelement composition, including calcium (9.50%), sodium (4.28%), magnesium (1.33%), phosphorus (6.37%), and potassium (21.91%). All microbiological indicators meet the requirements of GOST and indicate the absence of pathogenic microflora, which is one of the indicators of guaranteed sanitary well-being of the proposed products. The developed drinks have pleasant organoleptic indicators, high biological value and low cost price.

Peak factors of wind load for main frame design of rooftop structures

ABSTRACT Technology is being developed to unitize structures installed on apartment rooftops during construction. The rooftop is located at the top of a high-rise building with a flexible structure. However, the rooftop structure itself is close to a rigid body and is not integrated with the building. Therefore, it is difficult to calculate the gust effect coefficient of the rooftop structure. The peak factor provided by the Korean Design Standard (KDS) uses an equation for general buildings and may be inaccurate to a certain extent when used to calculate the wind load on rooftop structures. Therefore, in this study, wind pressure tests were conducted on three research models to calculate the appropriate peak factors for rooftop structures. For each model, the peak factor trend was analyzed according to the wind pressure coefficient, and the peak factor was presented. When the evaluation time was 10 min, the positive pressure peak factor converged to three and the negative pressure peak factor converged to four. Additionally, a formula for calculating the peak factor of rooftop structures based on the wind load evaluation time is proposed. Hence, the peak factor of rooftop structures can be calculated based on various evaluation times.

Deep learning-based minute-scale digital prediction model for temperature induced deflection of a multi-tower double-layer steel truss bridge

Bridge deflection serves as a vital and intuitive index for the evaluation of bridge safety. Temperature load has the greatest influence on the bridge deformation and studies on the temperature-induced deformation prediction of long-span bridge are in limited numbers. A digital prediction model based on deep learning in minute scale is established to study the bridge deflection caused by temperature. The wavelet transform (WT) is adopted to filter the high-frequency signals of the original deflection caused by the related load factors. Three different networks, long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and Transformer variant, are studied and compared in the prediction process. Two different learning strategies considering different input data are also considered to optimize the prediction performance. The proposed prediction model is applied to the temperature induced deflection prediction of a multi-tower double-layer steel truss bridge. The results show that strategy A, which employs temperature time series data as input, is less effective than strategy B. Incorporating both temperature and deflection data as inputs is essential for predicting temperature-induced deflections. Moreover, the Transformer-variant network generally exhibits superior prediction performance compared to the LSTM and Bi-LSTM. The self-attention mechanism of the Transformer allows it to focus on key historical temperature points, thereby enhancing prediction accuracy.

Measuring Teacher Personality Competence: Era 5.0 Challenges for Teachers in Indonesian Archipelago

Teachers in archipelagic regions face challenges such as limited access, geographical isolation, and cultural diversity, particularly in the Society 5.0 era. This study aims to assess the feasibility of an instrument for measuring teacher personality competency in this context. Using a quantitative approach, the study was conducted in Maluku Province, with a multistage random sample of 752 teachers from 94 schools. The instrument employed a modified four-point Likert scale, and data analysis was conducted using the PLS-SEM method to evaluate the measurement and structural models. Key findings include: 1) Exploratory Factor Analysis (EFA) identified six dominant factors and 29 items to measure teacher personality competency; 2) The measurement model demonstrated feasibility, with construct validity confirmed through convergent validity (loading factors 0.70 and Average Variance Extracted 0.50) and discriminant validity (Fornell-Larcker criterion and Heterotrait-Monotrait Ratio 0.90). Reliability was supported by Cronbach’s Alpha, Rho_A, and composite reliability values all exceeding 0.70. These results indicate that the instrument is suitable for assessing teacher personality competency in island regions, helping address the challenges of the Society 5.0 era. The study has important implications for Indonesian education stakeholders, providing a validated tool to guide teacher performance evaluations.

Uncovering the spatial characteristics of global net anthropogenic nitrogen input at high resolution and across 1.42 million lake basins

Global Net Anthropogenic Nitrogen Input (NANI) at high resolution is crucial for assessing the impact of human activities on aquatic environments. Insufficient global high-resolution data sources and methods have hindered the effective examination of the global characteristics and driving forces of NANI. This study presents a general framework for calculating global NANI, providing estimates at a 5-arc-minute resolution and over 1.42 million lake basins in 2015. The results highlight the region near the Tropic of Cancer as a concentration area for high NANI and an inflection point for latitude-based accumulation variation. It also emphasizes the uneven distribution of NANI among continents, with Asia and Africa having the highest proportions, yet their high and low values are notably lower than those of Europe and South America. A similar pattern is observed in global lakes, where Asia has the smallest quantity and volume, but the highest NANI intensity. In contrast, North America and Europe have larger quantities and volumes but the lowest NANI intensity. The global distribution characteristics reveal a clustering pattern in high and low values, with 1.25 % of the area having a sum of NANI exceeding 20 %. The uncertainty analysis regarding model parameters indicates that continents with the highest NANI do not always exhibit the highest uncertainty. These results bridge the gap between global nitrogen sustainable management and anthropogenic nitrogen input. They support research on spatiotemporal changes and controlling factors of global river nutrient loads, as well as the impact of climatic factors on basin nitrogen loss and its variability.

Design of a mix network with elliptic curve cryptography and XOR shuffling for secure communication with 5‐node

AbstractThis research paper proposes a novel 5‐node mix network, an anonymous communication network to boost privacy within the network. Within the proposed framework the crypto‐operations like encryption, decryption, and shuffling are held with the help of the Elliptic Curve Cryptography (ECC) and XOR algorithm. This unique combination helps to exchange the message within the communication network with enhanced security and privacy. To analyze the processing time and load factor at each intermediate node of mix network, an exhaustive experimental analysis is carried out for key sizes of 256, 384, and 512 bits respectively. These crypto‐operations like encryption, decryption, and XOR shuffling need varying time slots to perform at each intermediate node thereby having a varying load factor associated with them. The objective of this research is to analyze the processing time and load factor at each node within the 5‐node mix network thereby helping to analyze the strengths and weaknesses of each intermediate node. Through our analysis, these percentages are computed, shedding light on the allocation of computational load and resource utilization among the nodes.

Frost resistance of recycled aggregate concrete subjected to coupling sustained compressive load and freeze-thaw cycles

Recycled aggregate concrete (RAC) structures situated in cold regions are required to withstand the combined effects of mechanical load and environmental factors throughout their operational lifespan. The influence of sustained load introduces complexity to the degradation mechanism of RAC. This research examines the frost resistance of RAC across varying levels of recycled coarse aggregate (RCA) replacement (0, 50 %, 100 %) and sustained compressive loading (0, 0.3 fc, 0.5 fc). The frost resistance was quantified by the indices of macroscopic morphology change, mass loss, relative dynamic modulus of elasticity, and mechanical properties. Results show that 0.3 fc can effectively improve the frost resistance of RAC, a trend that becomes more pronounced with increasing replacement rates of RCA. Excessive stress (0.5 fc) was found to be unfavorable to the frost resistance of RAC and increase the compressive strength variability of RAC after freeze-thaw cycles. Analysis of meso/micro-structure characteristics using optical and scanning electron microscopes, along with the mercury intrusion porosimetry, reveals that optimal compressive loading (0.3 fc) enhances mortar integrity, reduces porosity, and improves compactness, thereby bolstering RAC’s frost resistance.

Experimental evaluation of novel gas liquid contactor packing based on triply periodic minimal surfaces (TPMS)

Additive manufacturing has widened the possibilities of design for gas–liquid packing geometries in recent years, allowing for new unexplored shapes. A novel design approach based on triply periodic minimal surfaces (TPMS11Triply periodic minimal surfaces.), an interesting class of smoothened curved surfaces, led to the conception of new periodic structures with complex geometrical features. The present study aims to assess the applicability of these new TPMS-based geometries as packing for gas–liquid contactors and the effect of their topology on performance. Liquid holdup, pressure drop, flooding and mass transfer efficiency were evaluated for three TPMS-based prototypes, with distinct characteristic dimensions. A new experimental setup was developed for the estimation of liquid holdup based on the measure of the liquid weight during operation by a set of load cells. Results show good repeatability and precision, allowing to distinguish liquid holdup between the prototypes for various gas and liquid flow rates. Two of the studied prototypes presented higher holdup than the 5 ppi ceramic foam and the 15 mm Raschig rings for lower liquid rates. Prototypes also showed good results for pressure drop, with flooding reached at gas load factors above 3Pa0.5. In terms of mass transfer efficiency, HETP results for the new prototypes remained between 0.35m and 0.45m, comparable to Mellapak 250Y.

Why are the railways of Eastern Europe less efficient than those of the West?

We use a DEA analysis to compare the efficiency of the railways of Western and Eastern Europe and find while most railways of Western Europe are on the efficiency frontier, those of Eastern Europe are typically a long way from it. One explanation may be that the reform process only started much later in Eastern Europe than in the West, although it appears that Eastern Europe has largely caught up. Secondly, Eastern Europe suffered a significant loss of traffic after the end of the communist regime, and this may still be resulting in an excess of labour and assets. There is some evidence that this remains the case for labour and freight vehicles. Although the excess of freight vehicles may be largely vehicles out of service, they still contribute to the poor efficiency scores for Eastern Europe. It is also the case that the countries of Eastern Europe suffer some disadvantages in terms of population density. However, we believe that two aspects of policy play an important role in the poorer performance of Eastern European countries compared with Western. Firstly, is the poorer infrastructure quality associated with lower levels of investment. This shows up as less use of electric traction and slower train speeds, resulting in lower productivity of staff and assets. Despite the efforts of the European Commission to overcome this problem, there is still a long way to go. Secondly, is the strong use of public service obligations to maintain high levels of service with relatively low load factors. If it is desired to raise the efficiency of Eastern European railways, governments in Eastern Europe will need to consider whether they are specifying excessively high levels of service.

Regulation of outer kinetochore assembly during meiosis I and II by CENP-A and KNL-2/M18BP1 in C. elegans oocytes

During cell division, chromosomes build kinetochores that attach to spindle microtubules. Kinetochores usually form at the centromeres, which contain CENP-A nucleosomes. The outer kinetochore, which is the core attachment site for microtubules, is composed of the KMN network (Knl1c, Mis12c, and Ndc80c complexes) and is recruited downstream of CENP-A and its partner CENP-C. In C.elegans oocytes, kinetochores have been suggested to form independently of CENP-A nucleosomes. Yet kinetochore formation requires CENP-C, which acts in parallel to the nucleoporin MEL-28ELYS. Here, we used a combination of RNAi and Degron-based depletion of CENP-A (or downstream CENP-C) to demonstrate that both proteins are in fact responsible for a portion of outer kinetochore assembly during meiosis I and are essential for accurate chromosome segregation. The remaining part requires the coordinated action of KNL-2 (ortholog of human M18BP1) and of the nucleoporin MEL-28ELYS. Accordingly, co-depletion of CENP-A (or CENP-C) and KNL-2M18BP1 (or MEL-28ELYS) prevented outer kinetochore assembly in oocytes during meiosis I. We further found that KNL-2M18BP1 and MEL-28ELYS are interdependent for kinetochore localization. Using engineered mutants, we demonstrated that KNL-2M18BP1 recruits MEL-28ELYS at meiotic kinetochores through a specific N-terminal domain, independently of its canonical CENP-A loading factor activity. Finally, we found that meiosis II outer kinetochore assembly was solely dependent on the canonical CENP-A/CENP-C pathway. Thus, like in most cells, outer kinetochore assembly in C.elegans oocytes depends on centromeric chromatin. However, during meiosis I, an additional KNL-2M18BP1 and MEL-28ELYS pathway acts in a non-redundant manner and in parallel to canonical centromeric chromatin.

Automatic hyperparameter tuning of topology optimization algorithms using surrogate optimization

This paper presents a new approach that automates the tuning process in topology optimization of parameters that are traditionally defined by the user. The new method draws inspiration from hyperparameter optimization in machine learning. A new design problem is formulated where the topology optimization hyperparameters are defined as design variables and the problem is solved by surrogate optimization. The new design problem is nested, such that a topology optimization problem is solved as an inner problem. To encourage the identification of high-performing solutions while limiting the computational resource requirements, the outer objective function is defined as the original objective combined with penalization for intermediate densities and deviations from the prescribed material consumption. The contribution is demonstrated on density-based topology optimization with various hyperparameters and objectives, including compliance minimization, compliant mechanism design, and buckling load factor maximization. Consistent performance is observed across all tested examples. For a simple two hyperparameter case, the new framework is shown to reduce amount of times a topology optimization algorithm is executed by 90% without notably sacrificing the objective compared to a rigorous manual grid search.

Degradation assessment of wind turbine based on additional load measurements

In recent years, there has been an increasing focus on the degradation assessment of wind turbines using supervisory control and data acquisition (SCADA) data, establishing condition monitoring as the preferred approach. However, SCADA data primarily focuses on general condition variables, such as temperature, while overlooking critical metrics like load factors for assessing the mechanical properties of wind turbines. The load parameters can be utilized to assess the mechanical stresses and strains experienced by wind turbine components, thereby offering more precise information on degradation. To address this gap, we explore the feasibility of implementing additional load monitoring for the degradation assessment of wind turbines. Specifically, we design a cost-effective load sensor system for collecting load data from wind turbines. On this basis, a novel degradation assessment method that incorporates additional load data and a nonlinear dynamic state-space neural network model is proposed to extract degradation information from wind turbines. Then, we introduce a dynamic degradation index, derived through trend analysis, which effectively captures and quantifies the degradation levels of wind turbines over time. Finally, a case study using a dataset collected from a real wind farm is provided to validate the proposed method. The results demonstrate a significant enhancement in degradation assessment. By incorporating additional load data, the proposed method exhibits heightened responsiveness to degradation levels and more effectively captures the progression of degradation trends.