Component Model Research Articles

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Influence of compatibilization methods on the compatibility between asphalt and DCLR components with molecular dynamics (MD) method

This study aims to investigate the effect of compatibilization methods on the compatibility between asphalt and direct coal liquefaction residue (DCLR) components to identify the key components in DCLR and asphalt that affect their compatibility. In this article, three types of compatibilizers, including benzyl alcohol (BA), dioctyl phthalate (DOP), and BA/DOP, were selected and acted on asphalt's components and DCLR's components, respectively. The molecular models of asphalt components, asphalt components with compatibilizers, DCLR components, and DCLR components with compatibilizers were established. The compatibility between DCLR and asphalt's four components, as well as between asphalt and DCLR's three components, were evaluated by solubility parameter difference (SPD) and interaction energy (IE). The compatibility between DCLR and asphalt was analyzed by Segregation test and Scanning Electron Microscope. Results indicate that the SPD and IE values between DCLR and asphalt components declined after adding compatibilizers, which implies that the repulsion decreased and the attraction increased between asphalt components and DCLR and the compatibility between asphalt components and DCLR improved. The IE values between DCLR components and asphalt increased after adding compatibilizers, which indicates that the compatibility was reduced between DCLR components and asphalt. The SPD values between DCLR components and asphalt increased after adding the BA/DOP. The SPD values between pre-asphaltene and asphalt decreased after adding the BA and DOP. The SPD value between asphaltene in DCLR and asphalt increased after adding the BA and decreased after adding the DOP. Moreover, the storage stability and homogeneity of DCLR-modified asphalt improved after adding compatibilizers, indicating that the compatibilizers enhanced compatibility between DCLR and asphalt. Finally, comparing the results of the tests, it could be found that compatibilizers preferentially acted on the asphalt components and mainly affected the aromatics in asphalt, thereby improving the compatibility between asphalt and DCLR. The effect of BA/DOP on improving the compatibility between asphalt and DCLR was better than that of BA and DOP.

Review of the creep constitutive models for rocks and the application of creep analysis in geomechanics

AbstractThe creep behavior of rocks has been broadly researched because of its extensive application in geomechanics. Since the time-dependent stability of underground constructions is a critical aspect of geotechnical engineering, a comprehensive understanding of the creep behavior of rocks plays a pivotal role in ensuring the safety of such structures. Various factors, including stress level, temperature, rock damage, water content, rock anisotropy, etc., can influence rocks’ creep characteristics. One of the main topics in the creep analysis of rocks is the constitutive models, which can be categorized into empirical, component, and mechanism-based models. In this research, the previously proposed creep models were reviewed, and their main characteristics were discussed. The effectiveness of the models in simulating the accelerated phase of rock creep was evaluated by comparing their performance with the creep test results of different types of rocks. The application of rock’s creep analysis in different engineering projects and adopting appropriate creep properties for rock mass were also examined. The primary limitation associated with empirical and classical component models lies in their challenges when it comes to modeling the tertiary phase of rock creep. The mechanism-based models have demonstrated success in effectively simulating the complete creep phases; nevertheless, additional validation is crucial to establish their broader applicability. However, further investigation is still required to develop creep models specific to rock mass. In this paper, we attempted to review and discuss the most recent studies in creep analysis of rocks that can be used by researchers conducting creep analysis in geomechanics.

Hydrostatic bearing groove multi-objective optimization of the gear ring housing interface in a straight-line conjugate internal meshing gear pump

The lubrication performance of a straight-line conjugate internal meshing gear pump is poor under the low-speed, high-pressure operating conditions of the volumetric servo speed control system, and it is difficult to establish a full fluid lubricating oil film between the gear ring and the housing. This leads to significant wear and severe heating between the gear ring and the housing. The lubrication performance of the interface moving pair of the electro-hydraulic actuator pump gear ring housing can be improved by designing a reasonable lubrication bearing structure for the gear ring housing. In this study, a multi-field coupling multi-objective optimization model was established to improve lubrication performance and volumetric efficiency. The whole model consists of the dynamic model of the gear ring components, the fluid lubrication model of the gear ring housing interface, the oil film formation and sealing model considering the influence of temperature, and the multi-objective optimization model. The comprehensive performance of the straight-line conjugate internal meshing gear pump was verified experimentally using a test bench. The results show that the lubrication performance is improved, the mechanical loss is reduced by 31.52%, and the volumetric efficiency is increased by 4.91%.

An Empirical Investigation of the Three-Pathway Model and its Contribution to the Gambling Disorder Psychopathology.

Blaszczynski and Nower (2002) proposed a theoretical model that leads to problem gambling via three pathways: (1) operant conditioning; (2) emotional vulnerability; and (3) impulsivity and psychopathy. In the current investigation, we explored the relationship between these three putative causative dimensions and clinical core features of Gambling Disorder (GD): gambling craving, gambling-related cognitive distortions, gambling (wagering) behavior, and gambling severity. Data on 343 people with disordered gambling were analyzed. Measures representing the three pathways were analyzed using principal component analysis (PCA). The PCA generated three profiles. The original dimension of impulsivity/psychopathy was divided into two parts; the impulsivity-related traits were combined with symptoms of depression and anxiety to form one single component representing a volatile emotional, cognitive and behavioral style, named the Affect-instability component. The other two components were Psychopathy and Operant Behavior. Linear regression models for each PCA component found that the Affect-instability component was associated with all core features of GD, i.e., craving, cognitive distortions, gambling behavior and severity (standardized Β range: 0.298-0.448, all p < 0.001). Operant Behavior was significantly associated with gambling behavior (standardized Β=-0.137, p = 0.038) and gambling severity (standardized Β=-0.157, p = 0.006). Psychopathy was associated only with gambling cognitive distortions (standardized Β=-0.300, p < 0.001), suggesting a wider dimension of cognitive challenges in GD. An instability component encompassing emotional and cognitive dysregulation was the strongest predictor of all clinical features of GD. The correlation between operant conditioning and gambling severity suggests that behavioral conditioning plays a role in the persistence of maladaptive gambling.

A Comprehensive Approach to Water Literacy in the Context of Climate Change

Anthropogenic climate change is impacting human survival through its impact upon water quality and availability. An urgent ethical imperative is thus raised for education policy makers and schools, particularly in the Australian and Asia Pacific regions, to adopt a curriculum to help students mitigate and adapt to the dire consequences caused by a warming planet. Through a blue transdisciplinary school curriculum, students will better understand and respond to the broader aspects of what is referred to as the hydrosocial cycle. A school move towards a blue curriculum requires educational policy to mandate an emphasis on the climate change effects upon the water cycle. An effective shift to a blue curriculum also requires that teachers’ ethical perspectives and sensitivities are sharpened through their tertiary education courses. This is needed so they develop confidence and pedagogy for teaching anthropogenic climate change generally, something still missing from Australian and other classrooms around the world, and, more specifically, for teaching the hydrosocial cycle. The Four Component Model of Ethical Decision Making is offered as a useful framework to guide teachers in examining their values and motivations when teaching potentially confronting topics such as the impacts of climate change upon the hydrosocial cycle.

Applying the human component model of parenting to other primates: Developmental patterns of mother-child interactions across primate species

The component model of human parenting has been extensively used to study parents’ interactions with their offspring and to examine variation across cultural contexts. The current study applies this model to nonhuman primates to investigate which forms of parenting humans share with other primates and how these interactions change over infants’ first year of life. We repeatedly observed 52 mother-infant pairs, including humans ( N = 11), chimpanzees and bonobos ( N = 21), and several species of small apes ( N = 20), during different daily activities when infants were 1, 6, and 12 months of age. Humans differed from apes in their higher probability of face-to-face contact and the use of object stimulation. Moreover, parenting seemed to be characterized by more variability within humans than within and possibly between ape species. Overall, the component model of parenting appears to be an effective tool to study the functional systems of parenting behavior in a comparative developmental perspective, by allowing direct comparisons between human and non-human primate species across development.

Node-level community detection within edge exchangeable models for interaction processes

Scientists are increasingly interested in discovering community structure from modern relational data arising on large-scale social networks. While many methods have been proposed for learning community structure, few account for the fact that these modern networks arise from processes of interactions in the population. We introduce block edge exchangeable models (BEEM) for the study of interaction networks with latent node-level community structure. The block vertex components model (B-VCM) is derived as a canonical example. Several theoretical and practical advantages over traditional vertex-centric approaches are highlighted. In particular, BEEMs allow for sparse degree structure and power-law degree distributions within communities. Our theoretical analysis bounds the misspecification rate of block assignments while supporting simulations show the properties of the network can be recovered. A computationally tractable Gibbs algorithm is derived. We demonstrate the proposed model using post-comment interaction data from Talklife, a large-scale online peer-to-peer support network, and contrast the learned communities from those using standard algorithms including degree-corrected stochastic block models, popularity-adjusted block models, and weighted stochastic block models.

Digital twin-enabled robust production scheduling for equipment in degraded state

Technological advancements are leading to a world where digital twins will become integral to manufacturing operations management. While wide-ranging applications of digital twins are being researched, robust production scheduling remains an enduring challenge, especially considering the numerous sources of uncertainty in a complex manufacturing system that can affect the validity of the obtained solution. Thus, the article proposes a Prognostics and Health Management (PHM)-enabled digital twin framework to perform job scheduling for a flow shop scheduling problem considering real-time equipment health state. The framework combines the adoption of a Genetic Algorithm optimizer with data-driven modelling leveraging algorithms like Principal Component Analysis and models like Discrete Event Simulation with the purpose to solve the engineering task of scheduling at hand. Building on such a technological blend, the framework incorporates the degradation and fault detection and diagnosis of failure modes across multiple components. The effect of degradation and faults on job processing times is learned as a distribution from the field data. The proposed framework is then validated in a laboratory environment where degradation is produced by inducing degradation and faults in the equipment. By means of various experiments, the optimized makespan is compared for the output schedules in different configurations. When equipment is degraded, production scheduling with PHM-enabled field-synchronized digital twin results in better makespan estimation, if compared to the digital twin without PHM. This shows the superiority of the framework in terms of more realistic makespan estimations, which finally corresponds to improved production schedule optimization, sensitive also to degraded states.

Hierarchical modelling of variance components makes analysis of resolvable incomplete block designs more efficient

The standard approach to variance component estimation in linear mixed models for alpha designs is the residual maximum likelihood (REML) method. One drawback of the REML method in the context of incomplete block designs is that the block variance may be estimated as zero, which can compromise the recovery of inter-block information and hence reduce the accuracy of treatment effects estimation. Due to the development of statistical and computational methods, there is an increasing interest in adopting hierarchical approaches to analysis. In order to increase the precision of the analysis of individual trials laid out as alpha designs, we here make a proposal to create an objectively informed prior distribution for variance components for replicates, blocks and plots, based on the results of previous (historical) trials. We propose different modelling approaches for the prior distributions and evaluate the effectiveness of the hierarchical approach compared to the REML method, which is classically used for analysing individual trials in two-stage approaches for multi-environment trials.

Cyclic modelling of T-joints with CHS chord members and passing-through plates

This paper focuses on modelling the cyclic response of welded T-joints between Circular-Hollow-Section (CHS) chords and passing-through plates. Recent works have highlighted that, in practical applications, this specific joint typology can be regarded either as a standalone connection or as a component representing one of the main sources of deformability and energy dissipation capacity in more complex beam-to-column joints with CHS columns and passing-through I-beams. Currently, research efforts have primarily focused on predicting the strength and stiffness of this type of connection. However, there is a knowledge gap regarding the characterization of the cyclic response of joints with passing-through members, a crucial aspect for modelling steel structures with these connection types in seismic areas.In light of this, the paper aims to characterize the cyclic response of T-joints with CHS members and passing-through plates using a comprehensive approach that incorporates experimental, numerical, and analytical methods. Initially, the results of an experimental study examining the cyclic behaviour of T-joint specimens with passing-through plates are presented. Subsequently, models of the tested joints are implemented in Finite Element software and validated against the experimental outcomes. The validated models are used to conduct a parametric study, considering 44 different configurations to obtain their force-displacement cyclic responses. These responses are mathematically modelled using the hysteretic uniaxial material from the OpenSees library and a Genetic Algorithm based tool previously developed by the authors (MultiCal). Finally, regression analyses are performed to develop formulations for predicting the mathematical parameters of the hysteretic uniaxial material model starting directly from the geometrical and mechanical properties of the connection.This approach enables designers to model the cyclic response in structural analysis with a straightforward approach, without the need for new calibrations or tests, if the modelled joints fall within the proposed range of calibration. From the point of view of the component modelling, the approach presented aligns with the larger research strand devoted to the extension of the component method codified in Eurocode 3 part 1.8 to cyclic loading conditions.

MODELS OF INTERCULTURAL COMPETENCE: COMPARATIVE ANALYSIS

MODELS OF INTERCULTURAL COMPETENCE: COMPARATIVE ANALYSIS

Oxygen targets following immediate percutaneous coronary intervention in comatose survivors of out-of-hospital cardiac arrest - a BOX sub-study

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The Novo Nordisk Foundation The Lundbeck Foundation. Background Treatment with supplemental oxygen in patients with acute myocardial infarction (AMI) has previously been associated with poorer outcomes. However, in patients with AMI resuscitated from out-of-hospital cardiac arrest (OHCA) and undergoing immediate revascularization, evidence regarding specific oxygen targets is sparse. Purpose To assess the impact of a restrictive versus a liberal oxygen target on infarct size in OHCA patients undergoing immediate percutaneous coronary intervention (PCI). Methods The current study is a sub-study of the BOX trial, a randomized trial with a 2-by-2 factorial design, in which comatose OHCA patients with a presumed cardiac cause of arrest were randomly assigned to either a restrictive oxygen target (partial pressure of arterial oxygen (Pao2) of 9 to 10 kPa) or a liberal oxygen target (Pao2 of 13 to 14 kPa). In this sub-study we included patients who underwent immediate revascularization with PCI. The primary outcome was myocardial infarct size as assessed by the cardiac enzyme troponin-T (TnT). TnT was measured repeatedly during the first 72 hours and analyzed with a repeated measures variance component model with baseline adjustment. Secondary outcome was one-year all-cause mortality assessed by Kaplan-Meier and Cox proportional hazards analyses. Results A total of 329 patients underwent immediate PCI, whereof 172 patients were randomized to the restrictive oxygen target and 157 to the liberal oxygen target. The oxygen intervention was successful with a significantly higher PaO2 in the liberal oxygen target group during the first 72 hours (p&amp;lt;0.0001). Baseline characteristics and findings on coronary angiography (CAG) were similar in the two oxygen target groups. Thus, median age was 63 (interquartile range (IQR) 55–71), 81% were male, and estimated left ventricular ejection fraction on arrival to hospital was 35% (IQR 25–45%). Further, 74% of the patients had an initial postresuscitation electrocardiogram with ST-segment elevations, and the left anterior descending artery was deemed as culprit lesion in 49% of the patients. There was no difference in peak TnT between the restrictive and liberal oxygen target group (median 2540 (IQR 925–6420) versus 3410 (792–8630), ng/l, p=0.23), nor did TnT differ between the groups during the first 72 hours after admission (Figure 1, p=1.00). Within one year from admission, 120 patients (36.5%) had died. There was no difference in mortality between the restrictive (34%) and liberal (39%) oxygen target group (hazard ratio, 0.80; 95% CI, 0.56-1.14; p=0.21) (Figure 2). Conclusion Targeting a restrictive versus a liberal oxygen level in comatose survivors of OHCA who underwent immediate revascularization did not affect infarct size nor did it result in a significant difference in one-year mortality rate.Figure 1:Troponin-T levelsFigure 2:Kaplan-Meier curves

Hyper-Flophet: A neural Prophet-based model for traffic flow forecasting in transportation systems

Nowadays, an accurate and reliable traffic forecast is meaningful in making the right decisions for traffic management systems in vehicular environments. Nevertheless, traffic flow prediction is a significant challenge in Vehicular Ad Hoc Networks (VANETs) that has taken much attention. Therefore, in this paper, we propose a hybrid traffic prediction model based on Prophet model and Long Short-Term Memory neural network (LSTM), called Hyper-Flophet, to predict next traffic flow. Hyper-Flophet model adopts the traditional neural prophet model but with major parameter tuning. First, we propose an efficient algorithm for predicting the traffic flow trend then, we develop an interactive LSTM (I-LSTM) model for auto-regression components. After that, we implement a new future regressor component called network mobility and finally, we enhance the event and holiday component by introducing exponential growth term. Through simulations with real VANET data, we show that the proposed hybrid approach can achieve superior forecasting performance over other models.

High dimensional variable selection through group Lasso for multiple function‐on‐function linear regression: A case study in PM10 monitoring

SummaryAnalyzing the effect of chemical and local meteorological variables over the behaviour in concentrations in the Abruzzo region (Italy), with the objective of forecasting and controlling air quality, motivates the current work. Given that the available data are curves that represent the day‐to‐day variations, a multiple function‐on‐function linear regression (MFFLR) model is considered. By assuming the Karhunen‐Loève expansion, MFFLR model can be reduced to a classical linear regression model for each principal component of the functional response in terms of all principal components (PCs) of the functional predictors. In this sense, a regularization approach for functional principal component regression based on the merge of functional data analysis with group Lasso is proposed. This novel methodology allows to estimate the model and, simultaneously, select those relevant functional predictors with the functional response, where each functional independent variable is represented by a group of input variables derived by the PCs.

Low-cycle fatigue behaviour of ribbed 1.4362 duplex stainless steel reinforcement

To investigate the fatigue behaviour of stainless steel (SS) reinforcement, monotonic tensile and cyclic fatigue loading tests on 1.4362 duplex SS bars with diameters of 12 mm, 16 mm, and 20 mm are conducted. To keep the characteristics of reinforcement used in engineering construction, the specimens remain unprocessed. Two loading schemes for cyclic tests are considered in this work: (i) constant strain-amplitude, and (ii) variable strain-amplitude. The Ramberg-Osgood model was used to fit the experimental results. The strain-based and energy-based fatigue life equations are obtained. The strain-based fatigue life equation is compared with the present fatigue life estimation equations. Moreover, the ReinforcingSteel material model in OpenSees is calibrated with the experimental data. The results show that SS bars under cyclic experience hardening followed by softening. The bar diameter does not significantly affect the fatigue life prediction. The modified fatigue life equation suggests that SS bars have better fatigue resistance than conventional steel (CS) bars. The numerical analysis indicates that the calibrated steel material model (i.e. ReinforcingSteel) can produce a good simulation of SS bars under cyclic loading. It can improve the accuracy of numerical models of concrete components reinforced by SS bars.

Modeling and Simulation of Unmanned Swarm System Based on Dynamic Structure DEVS

As a complex system with collaborative cooperation and capability emergence, the unmanned swarm system plays an important role in military, agriculture, aerospace and other fields. With the increasing complexity of unmanned swarm systems, traditional modeling methods cannot effectively describe the dynamics of swarm systems. In order to effectively design, use and evaluate unmanned swarm systems, this article conducts modeling and simulation of unmanned swarm systems based on DSDEVS(Dynamic Structure Discrete Event System Specification). Describe the unmanned swarm system from both behavioral and structural aspects. Based on component modeling, the microscopic behaviors of the unmanned platforms that constitute the unmanned swarm are described, and coupling relationships are established to describe the collaborative structure between unmanned platforms. According to the state transfer and event interaction characteristics of the unmanned swarm system, a synchronization mechanism is added to support changes in the swarm structure. This enables the unmanned swarm system to make adaptive structural adjustments according to environmental changes and its own goals during simulation operation, so as to achieve a state of enhanced capabilities and structural stability to complete the task. Finally, the effectiveness and feasibility of this method were verified through a simulation experiment of joint reconnaissance by a UAV swarm.

Hydrothermal hydrolysis of triglycerides: Tunable and intensified production of diglycerides, monoglycerides, and fatty acids

This study focuses on utilizing subcritical and supercritical water technology to produce intensive and selective diglycerides, monoglycerides, and fatty acids. The water properties can be easily modified by adjusting pressure and temperature, which promotes an improving solubility of the triglycerides in water and a selective production of glycerides. Triacetin and sunflower oil were used as models for short and long-chain components, exploring a range of temperatures (250 to 400 °C), pressures (22.0 to 25.0 MPa), and reaction times (0.7 to 29 s). A conversion of 98.5 % of sunflower oil is reached at 375 °C and 25.0 MPa in 29 s. The resulting products are 16.3 % diglycerides, 27.9 % monoglycerides, 48.9 % fatty acids, and 5.3 % glycerol. On the other hand, only 13 % of the oil is hydrolyzed at 300 °C, 22.0 MPa, with a reaction time of 23.6 s. The main product at this condition was fatty acids with a yield of 3.7 %. Furthermore, a kinetic model was developed to obtain comprehensive kinetic parameters for both raw materials to evaluate their reactivity during hydrolysis. This study provides valuable insights into the hydrolysis kinetics and the most promising conditions to make valuable products like fatty acids, mono and diglycerides, and glycerol.

Lightweight design of hydraulic excavator forearm

Taking the forearm of the hydraulic excavator as the research object, the working condition of the forearm is analyzed, the mathematical model of the forearm component is established, and the boundary load of the forearm is calculated. Altair Inspire software is used to conduct a simulation analysis of the preliminary design of the forearm components. According to the simulation results, the structure of the forearm is topologically optimized, and the optimized structure is verified. The results show that under the premise of not affecting the mechanical properties, the optimized structure is reduced by 36.32%, the load capacity is increased, and the production cost is reduced.

TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

The motor drives for aqua farms and large-scale irrigation system needs a reliable electric drive, which requires the continuous power supply and efficient control. However, the rural single phase power supply is frequently interrupted. Renewable assistance would improve the availability of supply and heuristic control approach improves robustness in control. This paper presents a three phase induction motor drive fed from single phase electric grid with assistance from PV and battery energy storage. TS- fuzzy based direct torque control is employed for robust control during load changes, and the topology, component modelling, front-end converter control, PV interface DC–DC converter control, and inverter control are presented. MATLAB/Simulink is used to simulate the proposed drive system. The performance of the proposed system is validated using simulation data for both steady-state and transient states.