Feasible Range Research Articles

Measuring overall functional diversity by aggregating its multiple facets: Functional richness, biomass evenness, trait evenness and dispersion

Abstract Human activities induce environmental changes, which can affect individuals' traits thereby leading to changes in functional diversity and finally in ecosystem functioning. Measuring functional diversity is thus of utmost importance to understand the consequences of such activities on ecosystem functioning. Functional diversity is composed of several facets, but these facets are almost always measured individually, and we lack a common metric integrating the multifaceted nature of functional diversity. Consequently, we developed an index defined as the geometric mean of four independent facets: functional richness (the classic measure of the coverage of the trait axis), biomass evenness and trait evenness (quantifying how evenly distributed the biomass and traits are among species and within the feasible trait range, respectively) and dispersion (quantifying the spread around the biomass‐weighted mean trait). and each of its underlying facet take values between 0 and 1, and they assume the uniform distribution to yield maximal diversity. We compared to other, more classic metrics measuring fewer facets of functional diversity by calculating all these indices for randomly and non‐randomly generated communities. We showed that overcomes several limitations of other indices (e.g. lack of accuracy, not computable for simple communities, unclear ecological interpretation) and is strongly correlated with ecosystem functions in simulated predator–prey communities. In addition, decomposing into its underlying facets revealed that ecosystem functions can be driven by different facets of on different trophic levels. The strength of our index lies in being the only index that measures accurately the overall functional diversity by combining several facets and providing the option to decompose into them. This notably yields mechanistic insights about which facets are more important for driving changes in functional diversity and ecosystem functioning.

Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation.

To overcome the restriction of identical distribution assumption, invariant representation learning for unsupervised domain adaptation (UDA) has made significant advances in computer vision and pattern recognition communities. In UDA scenario, the training and test data belong to different domains while the task model is learned to be invariant. Recently, empirical connections between transferability and discriminability have received increasing attention, which is the key to understand the invariant representations. However, theoretical study of these abilities and in-depth analysis of the learned feature structures are unexplored yet. In this work, we systematically analyze the essentials of transferability and discriminability from the geometric perspective. Our theoretical results provide insights into understanding the co-regularization relation and prove the possibility of learning these abilities. From methodology aspect, the abilities are formulated as geometric properties between domain/cluster subspaces (i.e., orthogonality and equivalence) and characterized as the relation between the norms/ranks of multiple matrices. Two optimization-friendly learning principles are derived, which also ensure some intuitive explanations. Moreover, a feasible range for the co-regularization parameters is deduced to balance the learning of geometric structures. Based on the theoretical results, a geometry-oriented model is proposed for enhancing the transferability and discriminability via nuclear norm optimization. Extensive experiment results validate the effectiveness of the proposed model in empirical applications, and verify that the geometric abilities can be sufficiently learned in the derived feasible range.

The heating effect analysis of electromagnetic induction heating system based on the multi objective optimization strategy

Lithium-ion battery heating in cold weather is necessary to ensure its low-temperature performance and lifetime, so the multi objective optimization heating strategy based on the non-dominated sorting genetic algorithm II is introduced to improve the heating effect of electromagnetic induction heating system, in which the generated Pareto frontier as the research sample is input in K-medoid algorithm in order to reduce the feasible range of solution sets and then get the optimal induction coil parameters combination, and the temperature rise and terminal voltage output performance of battery are characterized by the electrochemical-thermal coupling model. Firstly, under the optimal parameters combination (N = 180, f = 9 kHZ, IA = 6 A), the battery can be heated from 243.15 K to 293.15 K in 1430 s with the temperature difference of 2.74 K, and the temperature field is mainly generated by the heat conduction from active material to mandrel during the heating process due to skin effect and material property. Secondly, the internal resistance is decreased by more than 3 times after the heating, giving rise to the substantial improvement of energy output ability. Finally, neither noticeable discharging capacity retention loss nor apparent voltage output difference is founded after the 200 repeated heating cycles, as compared with the normal charging-discharging cycle at 293.15 K, so the heating strategy has almost no effect on the battery aging and lifetime deterioration. Therefore, the proposed heating strategy can realize a suitable tradeoff among temperature-rising effect, lifespan and low-temperature operating performance, which has substantial potential to be a feasible method for improving the applicability of electric vehicles in a cold weather.

CO2 transport in supercritical state: Nikiski, Alaska pipeline study

AbstractCarbon dioxide (CO2) in the supercritical state, being denser yet less viscous, is suitable for long‐distance transportation. Despite this well‐known principle, implementing an operational scheme with appropriate inlet pressure and mass flow rate for supercritical CO2 (srCO2) transportation is challenging due to the complex interplay among state variables, fluid properties, pipeline dimensions and materials, and the intricate boundary and ambient conditions surrounding the pipeline. This paper utilizes PIPESIM software to conduct a feasibility study of srCO2 transportation over a 10‐mile‐long model pipeline in the Cook Inlet region of Alaska, USA. The study aims to understand the limitations of operational parameters and develop a scheme for selecting feasible parameters for srCO2 transportation. Considering geographic location, elevation profiles, and ambient conditions, the simulations calculated pressure and temperature profiles, erosion kinetics, and fluid states for various conditions derived from a combinatorial set of pipeline diameters ranging from 11 to 16 in, inlet pressures between 1,400 and 1,900 psia, and mass flow rates from 10 to 275 lbm/s, with an inlet temperature of 200 °F. The major findings indicate that larger pressure losses are expected in smaller pipelines that are well‐insulated and/or operated at lower inlet pressures. Turbulent flow is more likely to occur in smaller pipelines and at higher mass flow rates, potentially altering the state of the transported fluid. The parametric modeling results provide a scenario‐driven approach to determining a feasible range of mass flow rates, pipeline inner diameters, and inlet pressures for srCO2 transportation. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

An Empirical Calibration of the Tip of the Red Giant Branch Distance Method in the Near Infrared. II. JWST NIRCam Wide Filters

The tip of the red giant branch (TRGB) is a standardizable candle, identifiable as the discontinuity at the bright extreme of the red giant branch (RGB) stars in color–magnitude diagram space. The TRGB-based distance method has been used to measure distances to galaxies out to D ≤ 20 Mpc with the Hubble Space Telescope F814W filter, and is an important rung in the distance ladder to measure the Hubble constant, H 0. In the infrared (IR), the TRGB apparent magnitude ranges from 1–2 mag brighter than in the optical. Now with the James Webb Space Telescope (JWST), the feasible distance range of the TRGB method can reach ∼50 Mpc. However, the IR TRGB luminosity depends to varying degrees on stellar metallicity/age. Here we standardize the TRGB luminosity using stellar colors as a proxy for metallicity/age to derive color-based corrections for the JWST Near-Infrared Camera short-wavelength filters F090W, F115W, and F150W, and the long-wavelength filters F277W, F356W, and F444W. We provide recommended filters for distance measurements depending on the requisite precision. For science requiring high precision (≤1% in distance), we recommend measuring the TRGB in F090W versus F090W − F150W or F115W versus F115W − F277W with the caveat that even with JWST, long integration times will be necessary at farther distances. If lower precision (>1.5% in distance) can be tolerated, or if shorter integration times are desirable, we recommend measuring the TRGB in either F115W or F150W. We do not recommend F444W for precision TRGB measurements due to its lower angular resolution.

Enhancement of optomechanical cooling via synthetic magnetism and frequency modulation.

We propose a scheme to enhance optomechanical cooling via synthetic magnetism and frequency modulation (FM) in a three-mode loop-coupled optomechanical system. By introducing synthetic magnetism, the dark-mode effect can be broken, ensuring the simultaneous cooling of the two mechanical resonators. We find that the cooling of the two mechanical resonators is destroyed in the dark-mode-unbreaking (DMU) regime but can be achieved in the dark-mode-breaking (DMB) regime. Furthermore, FM can be used to suppress the Stokes heating process, significantly enhancing the cooling performance and greatly expanding the feasible parameter range. In particular, in the unresolved-sideband (USB) regime, ground-state cooling of the two mechanical resonators can be achieved via FM even in the unstable region. Finally, we also study ground-state cooling in a multi-mode optomechanical network by breaking the dark-mode effect. Our work paves the way for exploring macroscopic quantum manipulation in multiple systems.

Modeling and analysis using piecewise hybrid fractional operator in time scale measure for ebola virus epidemics under Mittag–Leffler kernel

This emerging infectious disease poses one of the most severe threats to public health in these locations, but there are not many reliable therapies yet. In this work, we developed the Ebola virus dynamics and control factors epidemic model with a piecewise hybrid fractional Operator in time scale measure insight of Mittag–Leffler kernel. Patterns and structures that repeat at various scales are the focus of fractal analysis, which has applications in complex systems such as biological ones. Both qualitatively and statistically, a proposed model with the Lipschitz criteria and linear growth is examined, considering positive solutions, boundedness, and uniqueness at equilibrium points with Leray-Schauder results under time scale ideas. The regulation for linear responses approach will be used by Chaos Control to stabilize the system after its equilibrium points. A fractional-order framework with a controlled design will be considered, where solutions are bounded in the feasible domain of relations of different compartments. Ulam–Hyers stability results in the solution are treated when function (constant or rising) for the component of qualitative inquiry in generalized form. The dynamical behaviors of the suggested model are discussed with the Newton polynomial approach used to implement on model in the sense of classical piecewise and Mittag–Leffler kernel at different fractional order values. The model shows that solutions are stable and confined within a feasible range, ensuring reliability. Through detailed simulations, it effectively captures how different interventions and infection rates influence Ebola spread. This fractional-order model enhances understanding of Ebola transmission, providing a strong basis for predicting outbreaks and planning effective control measures, with practical applications for analyzing real-world data.

Cybernic robot hand-arm that realizes cooperative work as a new hand-arm for people with a single upper-limb dysfunction.

A robot hand-arm that can perform various tasks with the unaffected arm could ease the daily lives of patients with a single upper-limb dysfunction. A smooth interaction between robot and patient is desirable since their other arm functions normally. If the robot can move in response to the user's intentions and cooperate with the unaffected arm, even without detailed operation, it can effectively assist with daily tasks. This study aims to propose and develop a cybernic robot hand-arm with the following features: 1) input of user intention via bioelectrical signals from the paralyzed arm, the unaffected arm's motion, and voice; 2) autonomous control of support movements; 3) a control system that integrates voluntary and autonomous control by combining 1) and 2) to thus allow smooth work support in cooperation with the unaffected arm, reflecting intention as a part of the body; and 4) a learning function to provide work support across various tasks in daily use. We confirmed the feasibility and usefulness of the proposed system through a pilot study involving three patients. The system learned to support new tasks by working with the user through an operating function that does not require the involvement of the unaffected arm. The system divides the support actions into movement phases and learns the phase-shift conditions from the sensor information about the user's intention. After learning, the system autonomously performs learned support actions through voluntary phase shifts based on input about the user's intention via bioelectrical signals, the unaffected arm's motion, and by voice, enabling smooth collaborative movement with the unaffected arm. Experiments with patients demonstrated that the system could learn and provide smooth work support in cooperation with the unaffected arm to successfully complete tasks they find difficult. Additionally, the questionnaire subjectively confirmed that cooperative work according to the user's intention was achieved and that work time was within a feasible range for daily life. Furthermore, it was observed that participants who used bioelectrical signals from their paralyzed arm perceived the system as part of their body. We thus confirmed the feasibility and usefulness of various cooperative task supports using the proposed method.

Fermion masses and mixings and g − 2 muon anomaly in a Q6 flavored 2HDM

We propose an extended 2HDM with Q6×Z4×Z2 symmetry that can successfully accommodate the SM fermion mass and mixing hierarchy. The tiny masses of the active neutrinos are generated from a type-I seesaw mechanism mediated by very heavy right-handed Majorana neutrinos. The model gives a natural explanation of the charged lepton mass hierarchy. Besides that, the experimental values of the physical observables of the neutrino sector: the neutrino mass squared splittings, the leptonic mixing angles and the leptonic Dirac CP violating phase, are also successfully reproduced for both normal and inverted neutrino mass hierarchies. We find a feasible range of values for the leptonic Dirac CP phase to be in the ranges δCP∈(305.90,348.70)∘ for normal ordering and δCP∈(308.00,348.00)∘ for inverted ordering, which is consistent with the 3σ experimentally allowed limits. The sum of neutrino masses is obtained as ∑mi∈(58.03,60.51) meV for normal ordering and ∑mi∈(98.07,101.40) meV for inverted ordering which are well consistent with all the recent limits. In addition, the obtained ranges for the effective neutrino masses are 〈mee〉∈(3.80,4.38) meV, mβ∈(8.53,9.34)meV for normal ordering and 〈mee〉∈(47.85,49.58) meV, mβ∈(48.39,50.09)meV for inverted ordering which are in agreement with the recent experimental bounds. For the quark sector, the derived results are also in agreement with the recent data on the quark masses and mixing angles. The model under consideration can also accommodate the muon anomalous magnetic moment.

Optimal power dispatch method for wind farms considering service quality and available power

AbstractThis paper proposes an active and reactive power dispatch method for a wind farms (WF) considering the real‐time service quality and the available power to achieve the fair power allocation within the WF. The goal is to ensure operational safety while meeting the power demand instructions from the dispatch centre. This paper generates WF service quality metrics based on real‐time monitoring data of key components to characterize the operational stability of the wind turbines (WTs). Specifically, service quality metrics related to active/reactive power are constructed separately to improve the accuracy of service quality assessment and power dispatch. The available power is then integrated into the service quality metrics to derive active/reactive power allocation factors, considering operational safety and power margin. Active power allocation is constrained by the power demand instructions, while reactive power allocation aims to maintain the WT terminal voltage within a feasible range. The proposed method can ensure the fair power allocation within WFs to meet the requirements of equipment reliability, voltage safety, and power supply simultaneously, which can improve resource utilization and avoid the potential failure. Case studies in MATLAB/Simulink confirm the effectiveness of the proposed method.

Extracting Wetlands in Coastal Louisiana from the Operational VIIRS and GOES-R Flood Products

Visible Infrared Imaging Radiometer Suite (VIIRS) and Advanced Baseline Imager (GOES-R ABI) flood products have been widely used by the National Weather Service (NWS) for river flood monitoring, and by the Federal Emergency Management Agency (FEMA) for rescue and relief efforts. Some water bodies, like wetlands, are detected as water but not marked as permanent or normal water, which may result in their misclassification as floodwaters by VIIRS and GOES-R flood products. These water bodies generally do not cause significant property damage or fatalities, but they can complicate the identification of truly hazardous floods. This study utilizes the severe Louisiana flood event caused by Hurricane Ida to demonstrate how to differentiate wetlands from real-hazard flooding. Since Hurricane Ida made landfall in 2021, and there was no major flood event in 2022, VIIRS and ABI flood data from 2021 and 2022 were selected. The difference in annual total flooding days between 2021 and 2022 was calculated and combined with long-time flood frequency to distinguish non-hazard floodwaters due to wetlands identified from real-hazard floods caused by the hurricane. The results were compared with the wetlands from the change detection analysis. The confusion matrix analysis indicated an accuracy of 91.58%, precision of 89.97%, and F1-score of 76.63% for the VIIRS flood products. For the GOES-R ABI flood products, the confusion matrix analysis yielded an accuracy of 86.88%, precision of 97.49%, and F1-score of 75.21%. The accuracy and F1-score values for the GOES-R ABI flood products are slightly lower than those for the VIIRS flood products, possibly due to their lower spatial resolution, but still within a feasible range.

Inaccuracy principle and dissolution mechanism of lithium iron phosphate for selective lithium extraction from brines

The electrochemical lithiation/delithiation (ELD) method with the typical active materials being LiFePO4 and LiMn2O4, is the next generation technique for the selective lithium extraction from slat-lake brines owning to the advantages of high selectivity and excellent capacity and feasibility. However, the dissolution of LiFePO4/FePO4 (LFP/FP) during the ELD is seldom studied and an inaccurate measurement method for dissolution may result in obtaining an incorrect feasible application range for LFP/FP. Here, electrochemical workstation-electrochemical quartz crystal microbalance (EW-EQCM) is first utilized in the brine system to acquire the in-situ dissolution behavior of LFP/FP redox couple and verify the inaccuracy principle of the dissolution measurement. Both experimental results and thermodynamic calculations demonstrated that the accurate dissolution ratios can only be obtained by iron ions and phosphates at pH < 2.7 and pH < 5.3, respectively, which is induced by the narrow soluble range of iron ions and the formation of Ca5(PO4)3OH and Mg3(PO4)2 precipitation. In addition, the stable pH range of LFP and FP is 4 to 10 and 3 to 5, respectively, and the dissolution is caused by the formation of thermodynamically more stable metal ions, metal ion complexes, and metal ion hydroxides. At the optimum pH, the capacity can maintain 35 mg/g with average dissolution ratios of the cathode and anode lower than 0.1 %. This research sheds light on the accurate dissolution measurement range and method, dissolution mechanism and feasible application range of the LFP/FP redox couple.

Collaborative design of atmospheric cutterhead opening and disc cutter arrangement

As the core components of the shield machine, the cutterhead body and the cutter directly interact with the soil, which plays a vital role in tunneling efficiency and performance. For the atmospheric cutterhead, the cutterhead opening and the cutter arrangement are mutually restricted, which brings great challenges to the design of the cutterhead. To solve this problem, an innovative collaborative strategy for cutterhead structure and cutter arrangement is proposed in this paper. By constructing a parametric model, we deeply analyzed the relationship between the cutterhead parameters and the cutter size and defined the feasible range of parameter changes. On this basis, we have developed a set of cutter arrangement specifications to ensure the coordinated operation between the cutter holders and between the cutter holder and the gate, avoiding potential interference problems, and calculating the minimum cutter spacing. In addition, the study also takes into account the various loads on the cutter and constructs a load model specifically for the atmospheric cutterhead. By taking an atmospheric cutterhead with a diameter of 15 m as an example, we elaborate on the implementation process of this method, which not only maximizes the cutterhead opening but also effectively controls the unbalanced load. The methodology of this study provides a new perspective and solution for the design of other types of cutterhead.

Improved scheme of grid-connected inverters based on virtual PCC and impedance remodeling with enhanced steady-state and dynamic performance

The issue of low-frequency oscillation (LFO) becomes more prominent when considering the phase-locked loop (PLL) impact of grid-connected inverter (GCI) under weak grid. Impedance analysis shows that the frequency interaction point outside the capacitive negative damping region can effectively avoid the oscillation. Therefore, a modified PLL scheme is designed to shape the characteristics of the GCI output impedances, which effectively tracks the grid phase through the virtual point of common coupling and adjusts the phase- frequency characteristic of the GCI equivalent output impedance towards an increasing phase angle. On this basis, the impedance remodeling strategy is used to improve the system, which further broadens the feasible range of stable operation and ensures the phase margin of the GCI. The comparison results indicate that proposed scheme demonstrates enhanced capability in suppressing LFO and exhibits a wider range of adaptability to grid impedance. Experimental validation has verified the accuracy of the theoretical analysis, leading to the conclusion that the GCI with proposed scheme possesses superior dynamic performance.

Structure optimization and contact law study for transmission linkage of manipulator grasping fragile parts

According to the grasping requirements for fragile workpieces with cylindrical inner walls, a manipulator with internal bracing has been designed. The manipulator utilizes a constant-speed push cylinder to drive the linkage mechanism and accomplish the related works. Considering the fragile nature of the workpieces, reducing the impact velocity between the manipulator finger and the workpiece is a primary objective in the mechanism design. To achieve this, an optimization design is carried out, which maintains the overall average speed of the manipulator, while reducing the average speed only during the contact between the finger and the workpiece. The goal of optimization is to minimize the impact velocity at the contact point, using the linkage structure parameters as variables. The genetic algorithm (GA) is employed for the optimization process. The results show that optimization reduces the impact velocity at the contact point by 44.80%. To gain further insight into the influence of the process, a finite element model of a finger grasping a fragile object was created using joint modeling with the SolidWorks, Hyper Mesh, and LS-DYNA software. Simulations reveal that, after optimization, the maximum internal stress of three workpieces with thicknesses of 2.00 mm, 1.00 mm, and 0.50 mm was reduced by 47.42%, 41.53%, and 44.20%, respectively. To study the general law of the mechanical hand grasping fragile workpieces, the relationship between the cylinder driving speed and the impact speed is established. Based on the simulation results of maximum contact impact velocity, workpiece wall thickness, and maximum contact force, a prediction model of workpiece internal force is established using the Kriging prediction model theory. Additionally, the feasible range of grasping parameters under different wall thickness conditions is determined and discussed. The reliability of the designed structure is experimentally verified, providing valuable insights for ensuring the lifting work reliability of manipulators handling fragile workpieces.

Decentralized optimal voltage control for wind farm with deep learning-based data-driven modeling

The random fluctuations of wind energy and external grid voltage disturbances can both lead to serious voltage fluctuations and voltage deviations in the wind farm (WF). Voltage/reactive power control is an effective way to improve the voltage stability of WF. The existing research is based on complex physical models with prior parameter information, and the accuracy and calculation speed of the WF model are difficult to guarantee. To address this issue, this paper explores a decentralized optimal voltage control method for WF with deep learning-based (DL) data-driven modeling (DL-DOVC). A hybrid convolutional neural network (CNN)-Transformer architecture is proposed to establish the data-driven model of WF, leveraging its enhanced capabilities for extracting time series correlation, to learn complex patterns and dynamics from time series data. Then, we develop a fully decentralized voltage control method for WF to regulate the terminal bus voltage of wind turbines (WTs) within a feasible range. A DL-based data-driven predictive controller is specially designed to solve the established data-driven voltage optimization problem, it eliminates the necessity for frequent manual model maintenance and is suitable for real-time application. Additionally, the difficulty of WF decentralized optimal voltage control arises from the inability of local controllers to fully consider the impact of all non-local WTs on the local WT states. By designing the DL-based auxiliary state-feedback controller, the effects of non-local WTs are implicitly considered in the auxiliary feedback control law. A WF with 32*6.25 MW WTs is used to test the proposed DL-DOVC method. Simulation results show that the proposed DL-based model can efficiently learn and predict the WF dynamics under different operating scenarios. The near-global optimal voltage control performance is achieved only with local measurements by employing the DL-DOVC method.

Ductility‐oriented design of UHPC T‐beams: Mechanical model and design recommendations

AbstractUltrahigh performance concrete (UHPC) has recently become a major focus garnering substantial attention due to its remarkable mechanical properties. UHPC has been increasingly employed across diverse projects in the construction industry. However, the structural ductility of UHPC members has yet to be fully established and is often compromised by the manifestation of the crack localization phenomenon. This paper presents the flexural test results of five T‐beams and introduces a model for predicting the flexural capacity and failure modes of UHPC T‐beams. The model employs the curvature ductility index as a measurement for evaluating and ensuring the member's ductility. The results show that the flexural behavior of UHPC T‐beams can be characterized by four key points representing cracking, reinforcement yielding, crack localization, and post‐localization capacity. The validity of the model is substantiated by experimental data from this study and complemented by test data collected from the literature. The proposed model is then employed to derive ductility‐oriented design limits, including minimum and maximum reinforcement ratios and minimum localization strain capacity. Finally, the paper summarizes the design recommendations and provides a classification of section conditions, reinforcement limits, localization strain limits, adequate ductility range, and the feasible ductile design range.

A New Approach for Understanding International Hospital Bed Numbers and Application to Local Area Bed Demand and Capacity Planning.

Three models/methods are given to understand the extreme international variation in available and occupied hospital bed numbers. These models/methods all rely on readily available data. In the first, occupied beds (rather than available beds) are used to measure the expressed demand for hospital beds. The expressed occupied bed demand for three countries was in the order Australia > England > USA. Next, the age-standardized mortality rate (ASMR) has dual functions. Less developed countries/regions have low access to healthcare, which results in high ASMR, or a negative slope between ASMR versus available/occupied beds. In the more developed countries, high ASMR can also be used to measure the 'need' for healthcare (including occupied beds), a positive slope among various social (wealth/lifestyle) groups, which will include Indigenous peoples. In England, a 100-unit increase in ASMR (European Standard population) leads to a 15.3-30.7 (feasible range) unit increase in occupied beds per 1000 deaths. Higher ASMR shows why the Australian states of the Northern Territory and Tasmania have an intrinsic higher bed demand. The USA has a high relative ASMR (for a developed/wealthy country) because healthcare is not universal in the widest sense. Lastly, a method for benchmarking the whole hospital's average bed occupancy which enables them to run at optimum efficiency and safety. English hospitals operate at highly disruptive and unsafe levels of bed occupancy, manifesting as high 'turn-away'. Turn-away implies bed unavailability for the next arriving patient. In the case of occupied beds, the slope of the relationship between occupied beds per 1000 deaths and deaths per 1000 population shows a power law function. Scatter around the trend line arising from year-to-year fluctuations in occupied beds per 1000 deaths, ASMR, deaths per 1000 population, changes in the number of persons hidden in the elective, outpatient and diagnostic waiting lists, and local area variation in births affecting maternity, neonatal, and pediatric bed demand. Additional variation will arise from differences in the level of local funding for social care, especially elderly care. The problems associated with crafting effective bed planning are illustrated using the English NHS as an example.

What can go wrong in a dividing wall column and how to detect it

Dividing wall columns are state of the art distillation arrangements performing three separation tasks within one unit. Compared to using two conventional columns in series this saves both capital costs and energy but on the other hand it brings a higher risk of malfunction. This simulation study analyses what can go wrong during the operation of dividing wall columns. The emphasis is on the operation of the prefractionator section, that is, on the choice on the liquid and vapor splits, which is crucial for the overall performance. The resulting two-way flows between the prefractionator and main column gives a broader feasible operating range than in a conventional column arrangement. This can lead to peculiar behavior, including circulation of components around the dividing wall. This paper identifies 15 non-optimal operating regions for the prefractionator with specific internal flow patterns, characteristic temperature and composition profiles for the separation of a fairly ideal mixture of benzene, toluene and p-xylene. From these results it is possible to identify and hopefully rectify wrong choices for the liquid and vapor splits in a dividing wall column.

A Discrete Element Method Calibration Approach for Large Ore-flow Applications

The major constraint for large discrete element method (DEM) simulations is the high demand for computation power. To keep the model in a feasible range of simulation time and to conduct the numerical calculations efficiently, the implemented material can be simplified and upscaled. After this, a calibration of the material is inevitable and sets the link between the simulation model and reality. Therefore, an alternative calibration approach is established in this contribution to mimic the flow behaviour of the original material with multi-spherical DEM particles. The calibration approach utilises flow zone dimensions, which were observed in block-caving operations. Additionally, a passive draw-point is used to calibrate the angle of repose. Applying the calibration approach for Kiruna iron ore showed that, with the help of the calibration approach, the material in the simulation could successfully reproduce the targeted flow zone and angle of repose.