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The transition from fetal to newborn condition involves complex physiological adaptations for extrauterine life. A crucial event in this process is the clamping of the umbilical cord , which can be categorized as immediate or delayed. The type of clamping significantly influences the hemodynamics of the newborn. In this study, we developed a simulator based on existing cardiovascular models to better understand this practice. The simulator covers the period from late gestation to 24 h after birth and faithfully reproduces flow patterns observed in real-life situations (as evaluated by clinical specialists), considering factors such as the timing of cord clamping and the altitude of the birth location. It also reproduces blood pressure values reported in clinical data. Under similar conditions, the simulation results indicate that delayed cord clamping leads to increased oxygen concentration and improved blood volume compared to immediate cord clamping. Delayed cord clamping also had a positive impact on sustained placental respiration. Furthermore, this study provides further evidence that umbilical cord clamping should be based on physiological criteria rather than predefined time intervals. [Display omitted] • The model simulates pulmonary oxygen uptake and delivery across the alveolar-capillary membrane. • The model simulates placental oxygen uptake by incorporating oxygen consumption across the placental barrier. • The model simulates gas transport and consumption using new mathematical equations. • The model uses math to simulate the cessation of placental blood transfer following cord clamping. • It models neonatal transition at different altitudes, studying oxygen saturation impact. [ABSTRACT FROM AUTHOR]

In this paper, a novel Ultra-Wideband (UWB) Bandstop Filter (BSF) with five Transmission Zeros (TZ) and three Transmission Poles (TP) is presented. This filter is designed with a new type of resonator. Validation of the proposed filter with the lumped model is also investigated. Further, the transmission line circuit model of the filter is proposed, and consequently even and odd mode impedance is calculated analytically. Furthermore, a compact size of 16.8 mm × 14.98 mm (0.2λg × 0.18λg) is achieved by employing folded stubs. The proposed filter offers an Ultra-wide bandwidth of 7.5 GHz (2.9 –10.4 GHz) with a rejection depth of greater than 20 dB over the entire stopband. Moreover, the upper and lower skirt factors of 70 dB per GHz are achieved. A prototype of the proposed UWB BSF is fabricated and measured. Simulated and measured results are in good agreement, which validates the proposed design. [ABSTRACT FROM AUTHOR]

Predicting the operating temperature of lithium-ion battery during different cycles is important when it comes to the safety and efficiency of electric vehicles. In this regard, it is vital to adopt a suitable modeling approach to analyze the thermal performance of a battery. In this paper, the temperature of lithium-ion NMC pouch battery has been investigated. A new formulation of lumped model based on the thermal resistance network is proposed. Unlike previous models that treated the battery as a single entity, the proposed model introduces a more detailed analysis by incorporating thermal interactions between individual cells and tabs within a single cell scenario, while also considering interactions between cells and insulators or gaps, located between the cells, within the module case. This enhancement allows for the precise prediction of temperature variations across different cells implemented within the battery module. In order to evaluate the accuracy of the prediction, a three-dimensional finite element model was adopted as a reference. The study was performed first on a single cell, then on modules composed of several cells connected in series, during different operating conditions. A comprehensive comparison between both models was conducted. The analysis focused on two main aspects, the accuracy of temperature predictions and the computational time required. Notably, the developed lumped model showed a significant capability to estimate cell temperatures within the modules. The thermal results revealed close agreement with the values predicted by the finite element model, while needing significantly lower computational time. For instance, while the finite element model took almost 21 h to predict the battery temperature during consecutive charge/discharge cycles of a 10-cell module, the developed lumped model predicted the temperature within seconds, with a maximum difference of 0.42 °C. [ABSTRACT FROM AUTHOR]

Carbon-based materials, such as graphene, exhibit interesting physical properties and have been recently investigated in sensing applications. In this paper, a novel technique for glucose concentration correlation with the resonant frequency of a microwave resonator is performed. The resonator exploits the variation of the electrical properties of graphene at radio frequency (RF). The described approach is based on the variation in transmission coefficient resonating frequency of a microstrip ring resonator modified with a graphene film. The graphene film is doctor-bladed on the ring resonator and functionalised in order to detect glucose. When a drop with a given concentration is deposited on the graphene film, the resonance peak is shifted. The graphene film is modelled with a lumped element analysis. Several prototypes are realised on Rogers Kappa substrate and their transmission coefficient measured for different concentrations of glucose. Results show a good correlation between the frequency shift and the concentration applied on the film. [ABSTRACT FROM AUTHOR]

Predicting the operating temperature of lithium-ion battery during different cycles is important when it comes to the safety and efficiency of electric vehicles. In this regard, it is vital to adopt a suitable modeling approach to analyze the thermal performance of a battery. In this paper, the temperature of lithium-ion NMC pouch battery has been investigated. A new formulation of lumped model based on the thermal resistance network is proposed. Unlike previous models that treated the battery as a single entity, the proposed model introduces a more detailed analysis by incorporating thermal interactions between individual cells and tabs within a single cell scenario, while also considering interactions between cells and insulators or gaps, located between the cells, within the module case. This enhancement allows for the precise prediction of temperature variations across different cells implemented within the battery module. In order to evaluate the accuracy of the prediction, a three-dimensional finite element model was adopted as a reference. The study was performed first on a single cell, then on modules composed of several cells connected in series, during different operating conditions. A comprehensive comparison between both models was conducted. The analysis focused on two main aspects, the accuracy of temperature predictions and the computational time required. Notably, the developed lumped model showed a significant capability to estimate cell temperatures within the modules. The thermal results revealed close agreement with the values predicted by the finite element model, while needing significantly lower computational time. For instance, while the finite element model took almost 21 h to predict the battery temperature during consecutive charge/discharge cycles of a 10-cell module, the developed lumped model predicted the temperature within seconds, with a maximum difference of 0.42 °C.

Andesitic volcanic hydrosystems in Indonesia are mostly hydrogeologically unknown despite their socio-economic importance. The development of robust and easy-to-implement methodologies to conceptualize and quantify the water cycle components becomes a prerequisite for their sustainable management.We developed a lumped hydrological model to mimic the structure and functioning of a previously unknown hydrosystem located on the flanks of the Salak volcano (West Java). The structure of the aquifers was revealed with electrical resistivity tomography. The distinction between springs fed by the extensive artesian aquifer and others fed by shallow perched aquifers was obtained mostly using hydrochemistry. The elevation of the recharge area was identified using isotopic analysis of spring water.After designing the hydrological model structure, we carried out a probabilistic parameters exploration using the multiple-try differential evolution adaptive Metropolis algorithm to calibrate aquifer discharge. Multiple Markov chains allow a better exploration of the parameter values. The Bayesian approach provides the best water cycle simulation with a parameter uncertainty analysis, improving the accuracy and representation of the water cycle appropriate for previously unknown hydrosystems.

There has been growing interest recently in hybrid installations integrating the offshore wind farm and aquaculture farm as co-existence while optimizing ocean space use. The offshore marine farms beyond coastal or sheltered areas will require mooring to ensure the station-keeping of the farm system during the storms. In the present work, a sub-surface longline farm is installed in a fixed offshore wind farm at a distance from the wind foundations. The farm is designed to cultivate oysters in multi-compartment bags attached to the longlines vertically. The farm with a cultivating area of 200 m × 200 m is supported by the various farm lines made of polypropylene and buoys that is moored with catenary mooring arrangements. Drag coefficients of a full-scale oyster bag in wave and current are determined using the results of wave basin tests. A lumped model is developed and validated with a complete model for a partial farm. The lumped model is used to simulate the coupled responses of the whole farm in the site extreme waves and currents of a 50-year return period. The strength and fatigue designs of the mooring and farm lines are evaluated against the industry standards and confirmed to comply with the design requirements. [ABSTRACT FROM AUTHOR]

It is important to control the heating system by following real-time demand, while considering the dynamic changes and non-uniform distributions of indoor environments. This paper presents a model predictive control (MPC) scheme for predicting indoor air temperatures at multiple points in a large factory building that consists of large irregular spaces and heat-generating equipment. Instead of using a full-blown dynamic simulation model (e.g. EnergyPlus), the authors developed a lumped simulation model. This model can accurately predict the temperatures and is, therefore, used for the optimal on/off control of 61 unit heaters installed in the factory building. Based on the MPC, energy savings of 56.3% were realized over three weeks, and the indoor air temperatures were maintained within a comfortable range. It is highlighted in the paper that this MPC approach based on the minimalistic lumped model can accurately predict indoor thermal behaviour and save significant energy. [ABSTRACT FROM AUTHOR]

Weapons built on high-low pressure (HiLo) principle involve the existence of two chambers between which a gas flow occurs. The usual approach in the mathematical models developed for such systems is to consider that the gas flow is accompanied by an isothermal transformation of gas in the high pressure chamber. The present paper deals with the development of a lumped interior ballistic model built on more realistic assumptions like an adiabatic transformation of the gases in the high pressure chamber, an isentropic flow of real gases through the nozzles, a variable burning surface of the propellant grains and the occurrence of heat losses at the level of vent holes lateral surfaces. The experimental results obtained with a modified closed vessel were used in order to validate the proposed model. The pressure time variations in both chambers were accurately predicted by the proposed lumped model. The lumped model application on a 40 mm grenade launcher gives results consistent to the experimental measurements regarding the grenade muzzle velocity.

In this work, we present a methodology on automatic generation of predictive lumped sub-mechanisms for normal and branched alkanes. This methodology aims at obtaining lumped reaction mechanisms that preserve the chemical behavior of each reaction class in the detailed model. To achieve this goal, detailed sub-mechanisms for combustion of alkanes are generated by employing an updated version of the MAMOX++ software developed in this work; recent progress in the low-temperature reaction classes and rate rules are incorporated into the updated software. Instead of computing the selectivities of several primary products with MAMOX++ and fitting the selectivities between the detailed and lumped models, this work proposes a new methodology to generate the lumped sub-mechanisms for fuel molecules. The stoichiometric parameters and the reaction rates for each reaction class in the lumped sub-mechanism are fitted to match those in the detailed model. Based on the present methodology, both the detailed and lumped sub-mechanisms for normal C 5 C 10 alkanes and branched C 5 C 8 alkanes, that is for 15 different fuels, are automatically generated and merged into a base chemistry model (i.e. AramcoMech 2.0), respectively. The detailed and lumped models are validated against the experimental data in the literature. The automatically generated detailed models for alkanes are able to capture the experimental targets across a wide range of conditions, demonstrating the robustness of the reaction classes and rate rules adopted. The lumped models for normal alkanes have similar performance to their respective detailed models, and are able to predict the oxidation behavior of normal alkanes. However, prediction deviations between the detailed and lumped models for branched alkanes are shown to be slightly greater. [ABSTRACT FROM AUTHOR]

Pyrolysis is a low-emission and sustainable thermochemical technique used in the production of biofuels, which can be used as an alternative to fossil fuels. Understanding the kinetic characterization of biomass pyrolysis is essential for process upscaling and optimization. There is no accepted model that can predict pyrolysis kinetics over a wide range of pyrolysis conditions and biomass types. This study investigates whether or not the classical lumped kinetic model with a three-competitive reaction scheme can accurately predict the walnut shell pyrolysis product yields. The experimental data were obtained from walnut shell pyrolysis experiments at different temperatures (300–600 °C) using a fixed-bed reactor. The chosen reaction scheme was in good agreement with our experimental data for low temperatures, where the primary degradation of biomass occurred (300 and 400 °C). However, at higher temperatures, there was less agreement with the model, indicating that some other reactions may occur at such temperatures. Hence, further studies are needed to investigate the use of detailed reaction schemes to accurately predict the char, tar, and gas yields for all types of biomass pyrolysis. [ABSTRACT FROM AUTHOR]

Transient nonlinear heat conduction in a slab with temperature-dependent thermal conductivity, internal heat generation, and convective boundary conditions at both sides is analyzed by using the generalized integral transform technique (GITT) and an improved lumped parameter model. By adopting an appropriate eigenvalue problem, the dimensionless nonlinear heat conduction equation is integral-transformed into a set of coupled nonlinear ordinary differential equations in time, which is solved with a well-established numerical algorithm. The improved lumped parameter model is based on the Hermite approximations for integrals (H 1 , 1 / H 0 , 0). Excellent convergence of the GITT solution is shown, with its accuracy demonstrated by comparison with a reference finite difference solution. A good agreement between the lumped model and GITT solutions for the average temperature is shown. Parametric analysis is carried out to investigate the effect of the linear dependence coefficient β , heat generation parameter G , and Biot numbers on the average temperature. The average temperature increases with increasing heat generation parameter G , while decreases remarkably faster under larger linear dependence parameters β and Biot numbers. It is shown that the Biot numbers have a more significant impact on the average temperature than β. The proposed integral transform and lumped model solutions can be extended to one-dimensional problems in cylindrical and spherical coordinates, and to one-dimensional multilayered composite media. • Transient of heat conduction in a slab with temperature-dependent thermal conductivity is analyzed. • Internal heat generation and asymmetric convective cooling is modeled. • Benchmark solutions are obtained by using generalized integral transform technique (GITT). • Average temperature is obtained by Improved lumped model based on Hermite approximations for integrals. • Excellent convergence of GITT solutions and good agreement between GITT and improved lumped model solution are shown. [ABSTRACT FROM AUTHOR]

Carbon-based materials, such as graphene, exhibit interesting physical properties and have been recently investigated in sensing applications. In this paper, a novel technique for glucose concentration correlation with the resonant frequency of a microwave resonator is performed. The resonator exploits the variation of the electrical properties of graphene at radio frequency (RF). The described approach is based on the variation in transmission coefficient resonating frequency of a microstrip ring resonator modified with a graphene film. The graphene film is doctor-bladed on the ring resonator and functionalised in order to detect glucose. When a drop with a given concentration is deposited on the graphene film, the resonance peak is shifted. The graphene film is modelled with a lumped element analysis. Several prototypes are realised on Rogers Kappa substrate and their transmission coefficient measured for different concentrations of glucose. Results show a good correlation between the frequency shift and the concentration applied on the film.

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There has been growing interest recently in hybrid installations integrating the offshore wind farm and aquaculture farm as co-existence while optimizing ocean space use. The offshore marine farms beyond coastal or sheltered areas will require mooring to ensure the station-keeping of the farm system during the storms. In the present work, a sub-surface longline farm is installed in a fixed offshore wind farm at a distance from the wind foundations. The farm is designed to cultivate oysters in multi-compartment bags attached to the longlines vertically. The farm with a cultivating area of 200 m × 200 m is supported by the various farm lines made of polypropylene and buoys that is moored with catenary mooring arrangements. Drag coefficients of a full-scale oyster bag in wave and current are determined using the results of wave basin tests. A lumped model is developed and validated with a complete model for a partial farm. The lumped model is used to simulate the coupled responses of the whole farm in the site extreme waves and currents of a 50-year return period. The strength and fatigue designs of the mooring and farm lines are evaluated against the industry standards and confirmed to comply with the design requirements.

• A flexible model structure is developed to adopt various levels of complexity. • Necessity of considering different runoff generation process is tested. • Non-contributing model components and hypotheses are identified. • Complex model structure is found to be necessary for fast responding catchments. • For slow responding basins single reservoir model produces satisfactory results. Necessity of considering multiple processes involved in runoff generation at sub-hourly time scale is investigated using a flexible, lumped model structure. Runoff generation processes at hillslope scale are conceptualized at various levels of complexity and the contribution of the hillslopes is routed through the stream network to obtain the discharge at the basin outlet. Runoff generation is modelled using four conceptual interconnected reservoirs representing an interception storage, a high permeability storage of topsoil, a soil matrix storage, and a ground water storage. Alternate model versions are derived by eliminating or merging one or more of these storage components and adopting linear and nonlinear variations of the relationships of evaporation, infiltration and drainage with the storage. Split sample validation of each model version in three test catchments showed the contribution of individual model hypotheses and the associated components. A few hypotheses were found to be insignificant while others were found to have varying degree of influence on the accuracy of model predictions. Model parameters for the dominant processes could be reliably calibrated and less significant parameters are found to suffer from non-uniqueness. Comparison between two slow-responding and one fast-responding catchment showed that the relatively complex versions of the model were able to produce greater accuracy in all three test catchments, while the simpler versions showed good performance only in the slow responding catchments, failing to capture the quicker hydrological dynamics. Additionally, the redundant or non-dominant components were not found to be detrimental to model performance by any significant measure, however, computational effort or cost may be a consideration when deciding between a simple vs complex model structure. [ABSTRACT FROM AUTHOR]

• A lumped model was developed to describe the dynamic process of PM loading in the DPF. • The real-time wall porosity, collected soot mass, and pressure drop were predicted. • Effects of structural and operational factors on DPF performance was investigated. Particulate matter (PM) emitted from diesel vehicles poses significant risks to the global climate, environment, and human health. Diesel particulate filters (DPF) are currently the only effective aftertreatment device for PM emissions reduction, and it is important to reflect the DPF filtration and pressure drop performance by numerical method. This study established and validated a lumped model based on the spherical packed bed theory and Darcy's law. The model described the dynamic PM filtration process in DPF, predicting real-time characteristics such as wall porosity, soot load, and pressure drop with improved accuracy. The effects of channel characteristics, monolithic size, and exhaust conditions on filtration and pressure drop performance were also investigated. The results showed that an increase in cell density, wall thickness, DPF length, and diameter is beneficial for increasing filtration efficiency, while DPF inlet temperature and exhaust mass flow rate have adverse effects. Besides, wall thickness, DPF diameter and exhaust flow rate have a more significant impact on total pressure drop. The results improve the dynamic performance prediction in the PM filtration process and provide a theoretical basis for DPF structural optimization. [ABSTRACT FROM AUTHOR]

The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of 'Nash-Sutcliffe efficiency' and 'RMSE-observations standard deviation ratio' indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL's better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment. [ABSTRACT FROM AUTHOR]

The magnetic field inside a machine is responsible for the mechanical excitation of the stator structure, generating vibrations and thus, audible noise. In this article, the Permanent Magnet Synchronous Motor (PMSM) is driven by using sinusoidal pulsewidth modulation technique and then an investigation (cause and effect) of Acoustic Noise and Vibration (ANV) is presented. An equivalent lumped parametric modeling of end-to-end coaxially coupled shafts between PMSM and DC generator along with effective modal mass and modal participation factor accuracy enhancement technique is presented to predict the torsional vibration. The modal analysis approach is used to analyze the torsional vibration response, which is used to estimate the source of acoustic noise, and a mathematical approach is presented at the end to calculate ANV of electric drives. Theoretical and experimental investigations are carried out on a 1.07- kW, 4-poles, 36-slots, 3-phase PMSM drive. Analytical and numerical results are validated by experimental studies. [ABSTRACT FROM AUTHOR]

We suggest improving minimally-invasive stenosis severity estimation, using a combination of existing geometry-based methods with Transluminal Attenuation Gradient measurements. Instead of local flow values, the method uses flow distribution ratios along the entire tree. The tree geometry is used to derive a lumped model and predict the 'theoretical' ratios in each bifurcation, while attenuation measurements are used for extracting 'actual' ratios. The discrepancies between the measured and the theoretical values are utilized to assess a functional degree of stenosis. Our experimental and numerical analyses show that the quantitative value of discrepancy is proportional to stenosis severity, regardless of boundary conditions. [ABSTRACT FROM AUTHOR]

Traditional lumped small signal equivalent circuit models of AlGaN/GaN metal oxide semiconductor high electron mobility transistors (MOS-HEMTs) are made up of constant valued circuit elements. Such models are unable to capture the high frequency behavior (above 20 GHz) of the device. In this work, a modified small signal equivalent circuit model of AlGaN/GaN MOS-HEMTs is presented. The key feature of the proposed model is that the values of the different circuit elements in the model are considered to be frequency dependent in nature and not constants. The frequency dependent value of each circuit element is mathematically represented using polynomial functions where the coefficients of the functions are determined via a least-square curve fitting approach. This frequency dependent attribute of the circuit element values ensures that the proposed model is very accurate at high frequencies without sacrificing the compactness of the model topology. The accuracy of the proposed model has been verified up to 50 GHz using experimentally measured Y-parameters of AlGaN/GaN MOS-HEMTs having a different gate dielectric and gate length.

This paper investigates a parametric study on a novel type of flutter-based aeroelastic harvester by utilizing magneto-electro-elastic materials, which can be used as an alternative to piezoelectric materials in aeroelastic harvesters to enhance the output electric power. The considered model includes a deformable clamped beam attached to a rigid airfoil, covering with one or two magneto-electro-elastic layers. Connected electrodes to magneto-electro-elastic layers capture potential electric from the produced electric field. Furthermore, an extrinsic coil is wrapped around the vibrating beam to produce the magnetic-based electric energy in the applied magneto-electro-elastic layer. First, the harvesting system is modeled as a discrete model to derive the governing equations using Faraday and Gauss laws, and the constitutive equations of magneto-electro-elastic materials according to Hamilton's principle. Then, different configurations have been examined and compared. Afterward, the effect of various parameters on the chosen harvester characteristics is investigated through considering stability to determine the optimal parameters resulting in the highest electric power generation. Lastly, the efficiency of the magneto-electro-aeroelastic harvester is compared with a piezo-aeroelastic counterpart indicating the supremacy of the presented harvester. [ABSTRACT FROM AUTHOR]

This work provides an analytical non-linear model for the capacitive transduction in MEMS transducers with perforated counter-electrodes, especially applicable to capacitive MEMS microphones. Starting from an electrostatic description of a perforated unit cell of the transducer, analytical formulations of the variable capacitance and electrostatic forces are derived, accounting for the deflection profile of a clamped circular plate. A lumped implementation into conventional circuit simulations tools is enabled via behavioral modeling based on hardware description languages, such as Verilog-A. Therefore, the analytical model is approximated via Taylor series expansions, allowing for a stable and non-linear behavioral implementation. The resulting model finally enables both a small- and large-signal analysis of capacitive MEMS microphones, precisely accounting for non-linearities in the capacitive transduction. This allows to simulate the harmonic distortion of the microphone’s output signal and to account for electrostatic spring-softening in simulations of its bias voltage dependent sensitivity. [2020-0378] [ABSTRACT FROM AUTHOR]

Carbon based materials exhibit interesting mechanical, thermal and electrical properties which make them excellent contenders for use as fillers in composites as film. Graphene has been vastly used among the carbon-based materials. More recently eco-friendly carbon-based materials like biochar have emerged. The deployment of carbon-based materials in films needs to be studied since films are more versatile and permit the exploitation of electrical properties of such materials over circuits and systems. Typical circuits and systems exploiting electrical properties of novel materials perform a number of applications including sensing, detection, tunable devices and energy harvesting. In this paper, films composed of 9:1 graphene or biochar are deployed on a microstrip line. The morphological properties of graphene and biochar and their respective films are studied with Raman spectra and Field Emission Scanning Electron Microscope (FESEM). The electrical properties (four-point probe measurements and scattering parameter measurements) of the films. Low frequency measurements are used as starting point for circuit models estimating the lumped impedance of the films. From the morphological characterization it is shown that biochar films appear as granulates carbonaceous materials whereas graphene films contains several flakes forming a network. From the low frequency measurements and microwave characterization it is seen that graphene films are more conductive as compared to biochar films. In many applications, it is useful to know the surface impedance of the film since it varies on interaction with any external stimulus (variation of pressure, humidity, gas, etc.). [ABSTRACT FROM AUTHOR]

In general, electric ovens represent a low-efficiency class among home appliances, contributing to overall environmental changes in buildings and apartments. To improve their low efficiency, which is typically between 10% to 12%, industries are increasingly focused on developing effective technologies. One suitable strategy is to design and control the oven's center temperature, as specified by the EN 60350-1 European standard, which regulates the energy efficiency index (EEI) test. The present simulation study explains the transient thermo-fluid behavior of a domestic electric oven subjected to free convection, i.e., static mode. For this purpose, appropriate dynamic models are employed, intended for design and control. A lumped-parameter based methodology is considered to develop a low-order dynamic model, resulting in reduced computational cost and run time. A finite level of discretization is introduced into the model, enabling the capture of limited insights, such as temperature, heat flux, mass flow rate, pressure drop, etc., particularly at the cavity center, internal and external cavity wall surfaces, and at suction and exit openings. The electric oven is mainly divided into four sub-systems: door, cavity, ventilation, and cabinet. Each sub-system has a suitable level of discretization signifying a lumped mass parameter to reproduce the transient behavior within the electric oven. Heaters are considered as individual lumped masses and are integrated within the cavity sub-system. The above sub-systems employ both the first principle equations and correlations based on experimental data, giving a low-order grey-box identity to the system. In addition to conduction and convection, a non-linear form of radiation is considered to increase model accuracy. The developed model is further calibrated with available physical data. Once calibrated, the model is then compared with the remaining physical data produced at different heat loads to understand the accuracy in terms of transient temperature prediction at various temperature set points. • Developed a design and control model for empty cavity transient test. • Lumped parameter approach is implemented ensuring model accuracy and agility. • Model were calibrated and validated with experimental data. • All the non-linear terms were incorporated improving fidelity of model. [ABSTRACT FROM AUTHOR]

Pyrolysis of waste biomass represents a key route for the circular economy and a promising solution for the generation of valuable chemicals and liquid biofuels. The complex multi-component and multi-phase nature of the process, however, poses a challenge in acquiring comprehensive experimental data on biomass devolatilization. These data are essential for refining kinetic schemes and optimizing technology. This work presents a novel experimental methodology suitable for the collection of kinetically relevant data on biomass devolatilization combined with a complete characterization of the product slate. This methodology consists of a thermogravimetric analyser employed to carry out pyrolysis experiments, useful for the accurate monitoring of mass loss dependencies at varying heating rate, for the control of reaction temperatures and for the suppression of secondary gas-phase reactions as well as of transfer limitations. Multiple analytical methodologies and sampling protocols were combined for product speciation – downstream online MS for gases and H 2 O, sorbing traps for integral offline GC–FID/MS measurement of heavy oxygenates, point vapour collection for instant GC–FID/MS analysis of light oxygenates – and allowed to independently determine the integral mass yield of each pyrolysis product, closing mass balances with very high accuracy. Experiments of cellulose pyrolysis at varying heating rate were carried out to tune and validate the methodology. Speciation protocols allowed to identify and individually quantify 31 species among pyrolysis products, including gases, condensable oxygenates, H 2 O and char. The comparison of experimental findings with predictions from a state-of-art lumped model has highlighted the significance of the present methodology in unravelling the kinetics governing both devolatilization and product distribution. • A TGA-based methodology was developed for kinetic study of biomass pyrolysis. • Informative data on devolatilization kinetics were readily collected. • A combination of GC and MS analyses provided full speciation of pyrolysis products. • A total of 31 products were found and quantified in cellulose pyrolysis tests. • Limitations in available lumped models for product speciation were unveiled. [ABSTRACT FROM AUTHOR]

The Office of Hydrologic Development (OHD) of the U.S. National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) conducted the two phases of the Distributed Model Intercomparison Project (DMIP) as cost-effective studies to guide the transition to spatially distributed hydrologic modeling for operational forecasting at NWS River Forecast Centers (RFCs). Phase 2 of the Distributed Model Intercomparison Project (DMIP 2) was formulated primarily as a mechanism to help guide the U.S. NWS as it expands its use of spatially distributed watershed models for operational river, flash flood, and water resources forecasting. The overall purpose of DMIP 2 was to test many distributed models forced by high quality operational data with a view towards meeting NWS operational forecasting needs. At the same time, DMIP 2 was formulated as an experiment that could be leveraged by the broader scientific community as a platform for the testing, evaluation, and improvement of distributed models.DMIP 2 contained experiments in two regions: in the DMIP 1 Oklahoma basins, and second, in two basins in the Sierra Nevada Mountains in the western USA. This paper presents the overview and results of the DMIP 2 experiments conducted for the two Sierra Nevada basins. Simulations from five independent groups from France, Italy, Spain and the USA were analyzed. Experiments included comparison of lumped and distributed model streamflow simulations generated with uncalibrated and calibrated parameters, and simulations of snow water equivalent (SWE) at interior locations. As in other phases of DMIP, the participant simulations were evaluated against observed hourly streamflow and SWE data and compared with simulations provided by the NWS operational lumped model. A wide range of statistical measures are used to evaluate model performance on a run-period and event basis. Differences between uncalibrated and calibrated model simulations are assessed.Results indicate that in the two study basins, no single model performed best in all cases. In addition, no distributed model was able to consistently outperform the lumped model benchmark. However, one or more distributed models were able to outperform the lumped model benchmark in many of the analyses. Several calibrated distributed models achieved higher correlation and lower bias than the calibrated lumped benchmark in the calibration, validation, and combined periods. Evaluating a number of specific precipitation-runoff events, one calibrated distributed model was able to perform at a level equal to or better than the calibrated lumped model benchmark in terms of event-averaged peak and runoff volume error. However, three distributed models were able to provide improved peak timing compared to the lumped benchmark. Taken together, calibrated distributed models provided specific improvements over the lumped benchmark in 24% of the model-basin pairs for peak flow, 12% of the model-basin pairs for event runoff volume, and 41% of the model-basin pairs for peak timing. Model calibration improved the performance statistics of nearly all models (lumped and distributed). Analysis of several precipitation/runoff events indicates that distributed models may more accurately model the dynamics of the rain/snow line (and resulting hydrologic conditions) compared to the lumped benchmark model. Analysis of SWE simulations shows that better results were achieved at higher elevation observation sites.Although the performance of distributed models was mixed compared to the lumped benchmark, all calibrated models performed well compared to results in the DMIP 2 Oklahoma basins in terms of run period correlation and %Bias, and event-averaged peak and runoff error. This finding is noteworthy considering that these Sierra Nevada basins have complications such as orographically-enhanced precipitation, snow accumulation and melt, rain on snow events, and highly variable topography. Looking at these findings and those from the previous DMIP experiments, it is clear that at this point in their evolution, distributed models have the potential to provide valuable information on specific flood events that could complement lumped model simulations. © 2013.

The Office of Hydrologic Development (OHD) of the U.S. National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) conducted the two phases of the Distributed Model Intercomparison Project (DMIP) as cost-effective studies to guide the transition to spatially distributed hydrologic modeling for operational forecasting at NWS River Forecast Centers (RFCs). Phase 2 of the Distributed Model Intercomparison Project (DMIP 2) was formulated primarily as a mechanism to help guide the U.S. NWS as it expands its use of spatially distributed watershed models for operational river, flash flood, and water resources forecasting. The overall purpose of DMIP 2 was to test many distributed models forced by high quality operational data with a view towards meeting NWS operational forecasting needs. At the same time, DMIP 2 was formulated as an experiment that could be leveraged by the broader scientific community as a platform for the testing, evaluation, and improvement of distributed models.DMIP 2 contained experiments in two regions: in the DMIP 1 Oklahoma basins, and second, in two basins in the Sierra Nevada Mountains in the western USA. This paper presents the overview and results of the DMIP 2 experiments conducted for the two Sierra Nevada basins. Simulations from five independent groups from France, Italy, Spain and the USA were analyzed. Experiments included comparison of lumped and distributed model streamflow simulations generated with uncalibrated and calibrated parameters, and simulations of snow water equivalent (SWE) at interior locations. As in other phases of DMIP, the participant simulations were evaluated against observed hourly streamflow and SWE data and compared with simulations provided by the NWS operational lumped model. A wide range of statistical measures are used to evaluate model performance on a run-period and event basis. Differences between uncalibrated and calibrated model simulations are assessed.Results indicate that in the two study basins, no single model performed best in all cases. In addition, no distributed model was able to consistently outperform the lumped model benchmark. However, one or more distributed models were able to outperform the lumped model benchmark in many of the analyses. Several calibrated distributed models achieved higher correlation and lower bias than the calibrated lumped benchmark in the calibration, validation, and combined periods. Evaluating a number of specific precipitation-runoff events, one calibrated distributed model was able to perform at a level equal to or better than the calibrated lumped model benchmark in terms of event-averaged peak and runoff volume error. However, three distributed models were able to provide improved peak timing compared to the lumped benchmark. Taken together, calibrated distributed models provided specific improvements over the lumped benchmark in 24% of the model-basin pairs for peak flow, 12% of the model-basin pairs for event runoff volume, and 41% of the model-basin pairs for peak timing. Model calibration improved the performance statistics of nearly all models (lumped and distributed). Analysis of several precipitation/runoff events indicates that distributed models may more accurately model the dynamics of the rain/snow line (and resulting hydrologic conditions) compared to the lumped benchmark model. Analysis of SWE simulations shows that better results were achieved at higher elevation observation sites.Although the performance of distributed models was mixed compared to the lumped benchmark, all calibrated models performed well compared to results in the DMIP 2 Oklahoma basins in terms of run period correlation and %Bias, and event-averaged peak and runoff error. This finding is noteworthy considering that these Sierra Nevada basins have complications such as orographically-enhanced precipitation, snow accumulation and melt, rain on snow events, and highly variable topography. Looking at these findings and those from the previous DMIP experiments, it is clear that at this point in their evolution, distributed models have the potential to provide valuable information on specific flood events that could complement lumped model simulations. © 2013.

The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of ‘Nash-Sutcliffe efficiency’ and ‘RMSE-observations standard deviation ratio’ indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL’s better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment.

Previous studies tend to report the effect of rapid urbanization on temperature, but not on humidity. In this study, we aimed to address this research gap by examining diurnal profiles of temperature and humidity in Hong Kong. Our analysis revealed a more significant rising trend in humidity. In addition, our analysis of equivalent temperature revealed that latent temperature (i.e., moisture) contributes more to the aggravation of urban heat stress than does sensible temperature. The average urban air moisture concentration exceeds that in rural areas for both day and night, confirming the existence of an urban moisture island. A new lumped moisture model is developed to predict the hourly urban air humidity using weather data from the operational suburban weather stations, to better understand and quantify the urban moisture environment. The resulting coupled thermal‐moisture model can capture the main characteristics of diurnal profiles of urban air temperature and humidity in Hong Kong. The modelling results demonstrate that weakened city ventilation tends to lead to an increase in urban air moisture. Furthermore, natural surfaces (vegetation and bare soil) reduce urban heat stress by evapotranspiration. It is noteworthy that although the increase in fractions of natural surfaces can lead to more potential moisture sources, the absolute humidity will start to decrease when the fraction of natural surfaces reaches a threshold. This decreasing moisture trend may be attributable to reduced evaporation owing to the decreased surface temperature, reduced anthropogenic moisture and increased ventilation. Besides, the large wall areas in the compact high‐rise areas of Hong Kong function as both sinks and storage sites, contributing to a noticeable diurnal trend in the urban air humidity profile. In brief, the significant urban moisture island phenomenon in Hong Kong may result from enhanced evapotranspiration, restrained moisture sinks, intensive human activities and a weakened wind environment. [ABSTRACT FROM AUTHOR]

Long-term stream discharge data is indispensable in irrigation and drainage design. However, in Uganda, this data is poor and insufficient, limiting irrigation system design. Conversely, the rainfall monitoring network is denser than the river flow monitoring network. Therefore, we attempt to build a model that calculates river discharge from input of rainfall. In this study, the lumped parameter Tank Model was applied. The model was applied to the Namatala River catchment (155 km²) in Eastern Uganda. The study sought to ascertain the applicability of a lumped parameter model to a mid-sized catchment. Specifically, the objectives were: 1) To calibrate the numerical values of Tank Model parameters, 2) To verify the Tank Model parameters. This Tank Model required daily rainfall, evapotranspiration and river discharge data during calibration. Data for years 2015 and 2016 was used for calibration and validation respectively. During calibration, Monte Carlo simulation was used to find the numerical values of 16 Tank Model parameters. The best performing calibration parameter set had Nash-Sutcliffe (NS) efficiencies of 0.608 and 0.257 in calibration and validation respectively. However, among the 2015 calibration parameter sets, the one with a calibration NS of 0.502 performed best in validation (NS = 0.526). Equifinality was observed during parameter calibration. By using Tank Model, simulated discharge was divided into its surface runoff, interflow and base flow components. Tank Model was adaptable to Namatala River catchment. [ABSTRACT FROM AUTHOR]

In this work we analyze the impact of left ventricular assist devices on the systemic circulation in subjects with heart failure associated with left ventricular dilated cardiomyopathy. We use an integrated model of the left heart and blood flow in the systemic arteries with a left ventricular assist device. We study the impact of the rotation speed of the pump on haemodynamic characteristics of distal arteries. We identify the rotation speed for simultaneous recovery of the healthy average values in all systemic arteries, the heart and the aorta. Our numerical experiments show that blood distribution over the graph of systemic vessels does not depend on flow regimes in ascending aorta. We also observe that the optimal pump rotation speed changes in the atherosclerotic vascular network and depends on stenoses localization. [ABSTRACT FROM AUTHOR]

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Temperature prediction of a battery plays a significant role in terms of energy efficiency and safety of electric vehicles, as well as several kinds of electric and electronic devices. In this regard, it is crucial to identify an adequate model to study the thermal behavior of a battery. This article reports a comparative study on thermal modeling approaches by using a LiCoO2 26650 lithium-ion battery, and provides a methodology to characterize electrothermal phenomena. Three approaches have been implemented numerically--a thermal lumped model, a 3D computational fluid dynamics model, and an electrochemical model based on Newman, Tiedemann, Gu and Kim formulation. The last two methods were solved using ANSYS Fluent software. Simulations were validated with experimental measurements of the cell surface temperature at constant current discharge and under a highway driving cycle. Results show that the three models are consistent with actual temperature measurements. The electrochemical method has the lower error at 0.5C. Nevertheless, this model provides the higher error (1.3 °C) at 1.5C, where the maximum temperature increase of the cell was 18.1 °C. Under the driving cycle, all the models are in the same order of error. Lumped model is suitable to simulate a wide range of battery operating conditions. Furthermore, this work was expanded to study heat generation, voltage and heat transfer coefficient under natural convection. [ABSTRACT FROM AUTHOR]

Travel time distributions (TTDs) are concise descriptions of transport processes in catchments based on water ages, and they are particularly efficient as lumped hydrological models to simulate tracers in outflows. Past studies have approximated catchment TTDs with unimodal probability distribution functions (pdf) and have successfully simulated tracers in outflows with those. However, intricate flow paths and contrasting water velocities observed in complex hydrological systems may generate multimodal age distributions. This study explores the occurrence of multimodal age distributions in hydrological systems and investigates the consequences of multimodality for tracer transport. Lumped models based on TTDs of varying complexity (unimodal and multimodal) are used to simulate tracers in the discharge of hydrological systems under well‐known conditions. Specifically, we simulate tracer data from a controlled lysimeter irrigation experiment showing a multimodal response and we provide results from a virtual catchment‐scale experiment testing the ability of a unimodal age distribution to simulate a known and more complex multimodal age system. Models are based on composite StorAge Selection functions, defined as weighted sums of pdfs, which allow a straightforward implementation of uni‐ or multi‐modal age distributions while accounting for unsteady conditions. These two experiments show that simple unimodal models provide satisfactory simulations of a given tracer, but they fail in reproducing processes occurring at different temporal scales. Multimodal distributions, instead, can better capture the detailed dynamics embedded in the observations. We conclude that experimental knowledge of flow paths and the systematic use of data from multiple, independent tracers can be used to validate the assumption of water age unimodality. Multimodal age distributions are more likely to emerge in landscapes where the distributions of flow path lengths and/or water velocities are themselves multimodal. In general, age multimodality may not be particularly pronounced and detectable, unless comparable amounts of water with contrasting ages reach a given outflow. [ABSTRACT FROM AUTHOR]