Results Of Full Model Research Articles

Thermal hydraulic assessment on the full banana model of COOL blanket for CFETR

The Supercritical Carbon Dioxide (S-CO2) cOoled Lithium-Lead (COOL) blanket is under development for Chinese Fusion Engineering and Test Reactor. The thermal hydraulic assessment plays an important role for the comprehensive performance evaluation on the fusion blanket among the multi-physics fields. As the fusion reactor will enter into the engineering construction stage, it is important to study the thermal hydraulics performance on basis of the full model. Because it can accurately check the heat removal capability and thermoelectricity conversion efficiency, as well as provide essential input for the other physical fields. In this demand-driven, the analyses and optimization on the cooling system are put into priority on basis of the full banana model, including the manifold design and inlet/outlet pipes locations. Finally, the coolant pressure drop is highly reduced and the mass flow distribution becomes much more uniformly. For the S-CO2, 82.3% of the total mass flow rate is distributed into the key component first wall, and this is beneficial to face the high radiation heat flux. Besides, under different level of heat flux, the required total mass flow rate and pressure drop are obtained on premise that the coolant has enough ability to safely remove the heat away. For the Lead–Lithium (PbLi), the distribution of mass flow rate is designed as ‘ladder’ shape to adapt the unevenly spatial distributed nuclear heat along the radial direction, and the ratio is 8:2:1. Furthermore, the first law of thermodynamics is adopted for the trade-off analysis, which converts the total pressure drop of the two coolants into the pumping power, and it occupies only 1.3% of the total thermal power. This provides accurate and valuable data for the primary and secondary loop design, as well as the economic assessment on the fusion reactor. Finally, the Two Dimensional thermal hydraulic model containing the detailed layouts of different materials is used to study the coupling heat transfer effects between PbLi and S-CO2, as well as the MagnetoHydroDynamics (MHD) effects. The boundary conditions are derived from the results of full banana model, and the results show that the temperature of all materials is not exceeding the upper limits.

Research on Prediction of Breast Cancer Type using Machine Learning

The most typical cancer type among women worldwide is breast cancer. In 2020 alone, it afflicts about 0.68 million people and 6.9% of all cancer cases. How to categorize tumors as benign (non-cancerous) or malignant (cancerous) is one of the main obstacles to its diagnosis. This study helps to make an accurate and reliable diagnosis based on the initial data of the tumor, such as smoothness, texture, area using machine learning models. This study uses five machine learning models, Logistic Regression (RF), Random Forest (RF), Support Vector Machine (SVM), K-nearest Neighbor (KNN), Naive Bayes Classifier (NBC) and three modelling systems, feature selection-ML and principal component analysis (PCA)-ML system to make predictions of the type of the tumor of Wisconsin Breast Cancer Dataset. Model performance are assessed by three performance evaluation which are accuracy, precision, recall. The results of full model show that random forest has the highest prediction accuracy of 98.25% out of the sample and 100% in the sample, and SVM's sigmoid-based kernel model has the lowest prediction accuracy of 83.33% outside and 85.27% inside the sample. The results of the feature selection model based on RF and LR shows that the RF with only 13 variables has the highest prediction accuracy 98.25% out-of-sample and 100% in-sample. Among all the PCA--ML models, PCA--NBC has the highest prediction accuracy of 97.33% out-of-sample. Nevertheless, PCA-RF has the highest prediction accuracy of 100% in-sample.

Numerical optimization of highly loaded microtextured contacts: understanding and mastering complexity

PurposeMicrotextured surfaces can reduce friction in tribological systems under certain contact conditions. Because it is very time-consuming to determine suitable texture patterns experimentally, numerical approaches to the design of microtextures are increasingly gaining acceptance. The purpose of this paper is to investigate to what extent the selected modeling approach affects optimized texturing.Design/methodology/approachUsing the cam/tappet contact as an application-oriented example, a simplified 2D and a full 3D model are developed for determining the best possible texturing via a design study. The study explores elongated Gaussian-shaped texture elements for this purpose. The optima of the simplified 2D simulation model and the full 3D model are compared with each other to draw conclusions about the influence of the modeling strategy. The target value here is the solid body friction in contact.FindingsFor the elongated texture elements used, both the simplified 2D model and the full model result in very similar optimal texture patterns. In the selected application, the simplified simulation model can significantly reduce the computational effort without affecting the optimization result.Originality/valueDepending on the selected use case, the simulation effort required for microtexture optimization can be significantly reduced by comparing different models first. Therefore, an exact physical replica of the real contact is not necessarily the primary goal when it comes to texture selection based on numerical simulations.

Geometric design and optimization of scissor-type deployable structures

Geometric design is the essential first step to ensure transformation of a structure from an undeployed to a deployed state and vice-versa. Typically, this is achieved using motion criteria to prevent interference of parts. This paper describes the geometric design procedure of axisymmetric deployable structures made of planar angulated scissor units. The geometric design parameters are optimized not just using motion criteria but also structural performance measures. The first part of this paper discusses the refinement of geometric parameters, namely, shape equation, number of vertical layers, number of sectors in plan, and rise-to-span ratio, to ensure minimum change in span during deployment. Analysis results showed that more number of vertical layers, more sectors, and a lower rise-to-span ratio led to minimal changes in base radius during deployment. A finite element analysis of a simplified slice model was used to validate the results by comparing with the full three-dimensional model results. Genetic Algorithm was used to find the optimum number of vertical layers and sectors in plan based on structural performance. This paper presents results of concurrent optimization of layout, elevation, and member sizes of deployable domes to meet stiffness criteria and to reduce self-weight.

Browsing for food: Will COVID‐induced online grocery delivery persist?

The COVID‐19 pandemic altered daily activities. Many consumers reverted to online grocery shopping and home delivery. We analyze factors associated with the decision to grocery shop online and whether this will persist post‐COVID using data collected via a representative online Qualtrics panel in the State of New Jersey (N = 1,419). Around half of respondents either decreased in‐person shopping, increased online shopping, or pursued a combination of both. We used factor analysis to decompose attitudes towards the pandemic, finding that attitudinal responses broke down into ‘fearful’, ‘believers’, and ‘deniers’. Binomial regressions were used to analyze patterns of frequency of grocery shopping during the pandemic and changes in behavior during the pandemic. Results suggest that age, gender, ethnicity, educational attainment, having children at home, and attitudes towards COVID‐19 are likely to influence frequency of online and in‐person grocery shopping. Specifically, being 50 years or older is negatively associated with online grocery shopping. Those who deny COVID‐19 were less likely to decrease in‐person grocery shopping. People who had children at home, who had advanced degrees, or who were of Hispanic origin were more likely to increase online shopping and decrease in‐person shopping during the pandemic. While our results suggest that in‐person grocery shopping will return to prepandemic levels, we found that respondents report some increased persistence in online grocery shopping post‐COVID.

Reduced Order Model of Transactive Bidding Loads

Transactive energy (TE) has been identified to provide better grid efficiency and reliability by market-based transactive exchanges between energy producers and energy consumers. Simulations of TE systems are crucial to evaluate the benefits and impacts of different transactive mechanisms. However, such simulations can be time consuming due to the information exchange between various participants and complex co-simulation environments. In this paper, we develop a reduced order model to speed up the simulation of transactive systems in TE simulation platform (TESP) while achieving very low error between the reduced order and full model results. Specifically, the developed reduced order model consists of an aggregate responsive load agent which utilizes two Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTMs) to enable transactive elements to collectively participate in the TE system. The proposed aggregate responsive load (ARL) agent is able to produce similar transactive behaviors to the full simulation model while achieving significant simulation time reduction. We also show that the developed model enables generalization of simulation results across different dates and across different number of loads included in the simulations.

An epidemic model with transport-related infection incorporating awareness and screening.

In this paper, an SWEIQR epidemic model with transport-related infection is proposed. The model considers inter-patch travel with entry-departure screening. The reproduction number, R_{ed}^phi , is computed and analyzed with respect to awareness and screening parameters. The analytic computations show that the disease-free equilibrium in the absence of travel is globally asymptotically stable when R_omega le 1 and unstable otherwise. The trans-critical bifurcation occurs at R_omega =1 and the locally stable endemic equilibrium point appears if R_omega >1 near to R_omega =1. The numerical simulations are performed to verify the analytical computation and explore the dynamic behavior with respect to different model parameters. The result shows that disseminating awareness through the population reduces the spread of disease. Furthermore, the full model results show that the departure screening may reduce the spread of disease in each patch.

Model Reduction Techniques with RBE2 and RBE3 Connection for Structural Results of Handling/Lifting Fixtures for Satellite Payloads

A fixture is design to hold, support and locate every component with accuracy. Fixture design is very important step for the setup-planning phase. The present work aims to get proper result with accurate connection of the fixture. In this work, two techniques are built for fixture analysis, give the comparison of structural results of full model, and reduce model with connection of RBE 2 and RBE 3. Design and analysis of fixture is done by using known softwares, inventor and hyperworks.

Similarity of thermodynamic properties of the Heisenberg model on triangular and kagome lattices

Derivation of a reduced effective model allows for a unified treatment and discussion of the $J_1$-$J_2$ Heisenberg model on a triangular and kagome lattice. Calculating thermodynamic quantities, i.e. the entropy $s(T)$ and uniform susceptibility $\chi_0(T)$, numerically on systems up to effectively $N=48$ sites we show by comparing to full-model results that low-$T$ properties are well represented within the reduced model. Moreover, we find in the spin-liquid regime similar variation of $s(T)$ as well as $\chi_0(T)$ in both models down to $T \ll J_1$. In particular, the spin liquid appears to be characterized by Wilson ratio vanishing at low $T$, indicating on the low-lying singlet dominating over the triplet excitations.

Multispectral Remote Sensing Data Are Effective and Robust in Mapping Regional Forest Soil Organic Carbon Stocks in a Northeast Forest Region in China

Accurately mapping the spatial distribution information of soil organic carbon (SOC) stocks is a key premise for soil resource management and environment protection. Rapid development of satellite remote sensing provides a great opportunity for monitoring SOC stocks at a large scale. In this study, based on 12 environmental variables of multispectral remote sensing, topography and climate and 236 soil sampling data, three different boosted regression tree (BRT) models were compared to obtain the most accurate map of SOC stocks covering the forest area of Lvshun District in the Northeast China. Four validation indexes, including mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), and Lin’s concordance correlation coefficient (LCCC) were calculated to evaluate the performance of the three models. The results showed that the full variable model performed the best, except the model using multispectral remote sensing variables. In the full variable model, the regional SOC stocks are primarily determined by multispectral remote sensing variables, followed by topographic and climatic variables, with the relative importance of variables in the model being 63%, 28%, and 9%, respectively. The average prediction results of full variables model and only multispectral remote sensing variables model were 8.99 and 9.32 kg m−2, respectively. Our results indicated that there is a strong dependence of SOC stocks on multispectral remote sensing data when forest ecosystems have dense natural vegetation. Our study suggests that the multispectral remote sensing variables should be used to map SOC stocks of forest ecosystems in our study region.

The effect of gender-friendliness barriers on perceived image in nursing and caring behaviour among male nursing students.

To examine the relationships among nursing students' perceived nursing image, caring behaviours and gender-friendliness barriers to determine whether gender-friendliness barriers affect nursing image and caring behaviour among male nursing students. Because caring is typically seen as a feminine trait, male nurses face gender-role strains in the current nursing environment. Gender-friendliness barriers may have an impact on the vital relationship between professional nursing image and caring behaviour. This study used a quantitative and cross-sectional research design. Participants were 141 male students who had obtained at least 1month of clinical practice experience. We collected data using three instruments: The Caring Assessment Report Evaluation Q-sort (CARE-Q), Gender-Friendliness Barriers in Nursing Programs (GFB-NP), and Nursing Image-as a Profession Questionnaire (NIPQ). Data were collected from August 2016-July 2017. Partial least squares structural equation modelling (PLS-SEM) with bootstrapping was used to test the hypothesis model. The full model results indicated a direct positive and significant path from professional nursing image to caring behaviour (β=0.47, 95% CI=0.32 to 0.61, t=6.19, p<0.001). Gender-friendliness barriers had a direct and significant negative relationship between professional nursing image (β=-0.31, 95% CI=-0.49 to -0.12, t=3.17, p<0.01) and caring behaviour (β=-0.18, 95% CI=-0.35 to -0.02, t=2.18, p<0.05). In addition, the variable of student-perceived barriers to gender-friendliness was indirectly and significantly negatively related to caring behaviour (β=-0.15, 95% CI=-0.27 to -0.05, t=2.57, p<0.05) through professional nursing image. Male nursing students with a higher nursing image engage in greater caring behaviour. Gender-friendliness barriers, however, decrease students' nursing image and caring behaviour. As applied to nursing education, the goal should be to improve male nursing students' caring behaviours and professional nursing image and decrease gender-friendliness barriers.

Development of a Methodology for Interface Boundary Selection in the Multiscale Road Tunnel Fire Simulations

The simulation of large complex dynamical systems such as a fire in road tunnels is necessary but costly. Therefore, there is a crucial need to design efficient models. Coupling of computational fluid dynamics (CFD) models and 1D network modeling simulations of a fire event, a multiscale method, can be a useful tool to increase the computational efficiency while the accuracy of simulations is maintained. The boundary between a CFD model (near field) and a 1D model (far field) plays a key role in the accuracy of simulations of large systems. The research presented in this paper develops a novel methodology to select the interface boundary between the 3D CFD model and a 1D model in the multiscale simulation of vehicle fire events in a tunnel. The development of the methodology is based on the physics of the fluid structure, turbulent kinetic energy of the dynamical system, and the vortex dynamics. The methodology was applied to a tunnel with 73.73 m2 cross section and 960 m in length. Three different vehicle fire scenarios were investigated based on two different heat reslease rates (10 MW and 30 MW) and two different inlet velocities (1.5 m/s and 5 m/s). all parameters upstream and downstream of the fire source in all scenarios were investigated at t = 900 s. The effect of changes in heat release rate (HRR) and air velocity on the selection of an interface boundary was investigated. The ratio between maximum longitudinal and transversal velocities was within a range of 10 to 20 in the quasi-1D region downstream of the fire source. The selected downstream interface boundary was 12Dh m downstream of the fire for the simulations. The upstream interface boundary was selected at 0.5 Dh m upstream the tip of the object when the velocity was greater than equal to the Vc. In the simulations with backlayering (V < Vc), the interface boundary was selected 10 m further from the tip of the backlayering (1.2 Dh). An indirect coupling strategy was utilized to couple CFD models to 1D models at the selected interface boundary; then, the coupled models results were compared to the full CFD model results. The calculated error between CFD and coupled models for mean temperature and velocity at different cross sections were calculated at less than 5%. The findings were used to recommend a modification to the selection of interface boundary in multiscale fire simulations in the road tunnels and more complex geometries such as mines.

Simplification workflow for hydraulically fractured reservoirs

Abstract Production from unconventional formations, such as shales, has significantly increased in recent years by stimulating large portions of a reservoir through the application of horizontal drilling and hydraulic fracturing. Although oil shales are heavily dependent on oil prices, production forecasts remain positive in the North-American region. Due to the complexity of hydraulically fractured tight formations, reservoir numerical simulation has become the standard tool to assess and predict production performance from these unconventional resources. Many of these unconventional fields are immense, consisting of multistage and multiwell projects, which results in impractical simulation run times. Hence, simplification of large-scale simulation models is now common both in the industry and academia. Typical simplified models such as the “single fracture” approach do not often capture the physics of large-scale projects which results in inaccurate results. In this paper we present a simple, yet rigorous workflow that generates simplified representative models in order to achieve low simulation run times while capturing physical phenomena which is fundamental for accurate calculations. The proposed workflow is based on consideration of representative portions of a large-scale model followed by post-process scaling to obtain desired full model results. The simplified models that result from the application of the proposed workflow for a single well and a multiwell case are compared to full-scale models and the “single fracture” model. Comparison of fluid rates and cumulative production show that accurate results are possible for simplified models if all important components for a particular case are taken into account. Finally, application of the workflow is shown for a heterogeneous field case where prediction studies can be carried out.

Why do you adopt social networking sites?

PurposeThe purpose of this paper is to investigate those factors that are associated with the adoption of social networking sites from the perspective of Muslim users residing in Malaysia.Design/methodology/approachA complete self-administered questionnaire was collected from 223 Muslim users of social networking sites in Malaysia. Both exploratory and confirmatory factor analyses were used to sort the significant items for the constructs and to check the validity. Structural equation modelling was applied in testing the hypotheses and the fitness of the proposed model.FindingsThe results of full structural model attest that technological and social factors are the most significant factors behind the adoption of social networking sites. However, this is followed by an educational factor. Among Muslim users in Malaysia, the study does not find significant influence of brand or product communication behind this adoption.Originality/valueThe paper investigates those factors that are considered inevitable in the adoption of social networking sites. Invaluable findings were offered in the form of a structural model for the stakeholders of social networking sties. These findings can be used in planning and making decisions that may benefit all parties associated with it.

Spatial clustering and halo occupation distribution modelling of local AGN via cross-correlation measurements with 2MASS galaxies

We present the clustering properties and halo occupation distribution (HOD) modelling of very low redshift, hard X-ray-detected active galactic nuclei (AGN) using cross-correlation function measurements with Two-Micron All Sky Survey galaxies. Spanning a redshift range of $0.007 < z < 0.037$, with a median $z=0.024$, we present a precise AGN clustering study of the most local AGN in the Universe. The AGN sample is drawn from the SWIFT/BAT 70-month and INTEGRAL/IBIS eight year all-sky X-ray surveys and contains both type I and type II AGN. We find a large-scale bias for the full AGN sample of $b=1.04^{+0.10}_{-0.11}$, which corresponds to a typical host dark matter halo mass of $M_{\rm h}^{\rm typ}=12.84^{+0.22}_{-0.30}\,h^{-1} M_{\odot}$. When split into low and high X-ray luminosity and type I and type II AGN subsamples, we detect no statistically significant differences in the large-scale bias parameters. However, there are differences in the small-scale clustering which are reflected in the full HOD model results. We find that low and high X-ray luminosity AGN, as well as type I and type II AGN, occupy dark matter haloes differently, with 3.4$\sigma$ and 4.0$\sigma$ differences in their mean halo masses, respectively, when split by luminosity and type. The latter finding contradicts a simple orientation-based AGN unification model. As a by-product of our cross-correlation approach, we also present the first HOD model of 2MASS galaxies.

Quasilinear diffusion coefficients in a finite Larmor radius expansion for ion cyclotron heated plasmas

In this paper, a reduced model of quasilinear velocity diffusion by a small Larmor radius approximation is derived to couple the Maxwell's equations and the Fokker Planck equation self-consistently for the ion cyclotron range of frequency waves in a tokamak. The reduced model ensures the important properties of the full model by Kennel-Engelmann diffusion, such as diffusion directions, wave polarizations, and H-theorem. The kinetic energy change (Ẇ) is used to derive the reduced model diffusion coefficients for the fundamental damping (n = 1) and the second harmonic damping (n = 2) to the lowest order of the finite Larmor radius expansion. The quasilinear diffusion coefficients are implemented in a coupled code (TORIC-CQL3D) with the equivalent reduced model of the dielectric tensor. We also present the simulations of the ITER minority heating scenario, in which the reduced model is verified within the allowable errors from the full model results.

Reduced-order model of cascade-type PEM fuel cell stack with integrated humidifiers and water separators

In this paper, model order reduction (MOR) of cascade-type polymer electrolyte membrane (PEM) fuel cell stack with integrated humidifiers and water separators is investigated. The purpose of this work is to attain orders of magnitude improvement in numerical simulation speed. Both the anode and the cathode of stack operate in a dead-end mode. The reduced-order model (ROM) is developed for continuous and discrete form of the cascade-type PEM fuel cell models. The obtained ROM is verified with the full nonlinear model, which full-order model itself is validated using experimental data from cascade-type 4-cells PEM fuel cell stack. Responses of different orders of ROMs are compared to those of full-order model to determine the minimum order of the model that approximates the behavior of the original model properly. The results predicted by the developed reduced-order model nearly follow the full nonlinear model and experimental results. According to the low computational cost of ROM, the derived model can be further used for real-time control and diagnostic applications.

Simulation model of the LNG carrier with podded propulsion, Part II: Full model and experimental results

The presented paper is the second part of the work devoted to the simulation model of the ship dynamics. The block oriented model was created and written as the S-function in the Matlab package and consists of the subsystems describing hydrodynamics forces, forces from two pods, two bow thrusters and wind. The values of all model parameters are also given. The results of the representative set of experiments preformed with the real vessel and its simulation model are shown at the last part of the paper. The attempt to estimate the model accuracy is presented at the end.

Towards an integrative picture of human sickness behavior

Sickness behavior, a coordinated set of behavioral changes during infection and elicited by the pro-inflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β), is well studied in non-human animals. Over the last two decades, several papers have expanded this research to include humans. However, these studies use a variety of research designs, and typically focus on a single cytokine and only a few of the many behavioral changes constituting sickness behavior. Therefore, our understanding of human sickness behavior remains equivocal. To generate a more holistic, integrative picture of this phenomenon, a meta-analysis of the human sickness behavior literature was conducted. Full model results show that both IL-6 and IL-1β have significant relationships with sickness behavior, and the strength of these relationships is affected by a number of study parameters, such as type of immune stimulus and inclusion of controls. In addition to research design heterogeneity, other issues to address in future studies include an unequal focus on different cytokines and different sickness behaviors.

Prioritizing Energy Sources to Generate Electricity (Application of Fuzzy Logic)

Organizations, institutions, and different sectors of manufacturing, services and agriculture are constantly making decisions. Each of the aforementioned sectors, have strategies, tactics, and various functions that play a basic role in reaching the objectives. On the other hand, energy demand in developing countries is increasing day by day. The exact calculation of the cost per unit of electricity generated by power plants is not easy. Therefore, this study according to four sources of natural gas, nuclear energy, renewable energy and other fossil fuels other than natural gas that are used in a variety of electricity production plants is trying to clarify the ranking of generation electricity approach using "fuzzy preference relations" analysis. Accordingly, three models were used and the results showed that natural gas, with regard to the four criteria of low investment cost, low power, lack of pollution and the safety and reliability of electrical energy has priority over other alternatives. Full preferred model results also suggested that the energy of natural gas, renewable energies, nuclear and other fossil fuels should be considered in a priority for power generation. Sensitivity analysis results moreover demonstrated that the above models are not affected by the threshold values ​​and the full stability of the models is observed.