Simple Lumped Model Research Articles

Signal growth in a pure time-modulated transmission line and the loss effect

We present the first comprehensive study for signal growth in transmission lines (TL) with purely time-modulated characteristic impedance Z o (infinite superluminality). This study pioneers the investigation into the effects of varying the cell’s electrical length and the impact of loss on momentum bandgaps and amplification levels. It also thoroughly examines how time-modulated transmission line truncation by a static load influences the sensitivity of amplification gain to the relative phase between the incoming signal and modulation, comparing these findings with the case of parametric amplification. Varying Z o is accomplished by loading TLs with a sinusoidally time-modulated capacitor (TMC). The study starts with a simple lumped model cell to facilitate understanding of the phenomena. Following this, transmission lines are introduced, and the effects of incorporating loss are examined. To accomplish this, three models are investigated: a lossless L-C TL lumped model loaded with a shunt lossless TMC and a TL loaded with a shunt lossless and lossy TMC. Dispersion diagrams are plotted and momentum bandgaps are identified at a modulation frequency double the signal frequency. Within the momentum bandgap, only imaginary frequencies are found and correlated to momentum bandgap width and signal growth level. Signal growth is confirmed using harmonic balance and transient simulations, and the results are consistent with the dispersion diagram outcomes.

Key controls on water transit times along a tropical precipitation gradient

The tropics are one of the most diverse and dynamic regions on Earth. Despite their importance, our understanding of tropical hydrological processes remains a significant challenge, mostly due to limited monitoring. Here, we used high-resolution daily input–output isotope data sets from seven tropical catchments ranging in size from 1.6 to 990 km2, situated within a precipitation gradient ranging from on average 958 to 5117 mm year−1, in Australia, Costa Rica, and Ecuador. For these catchments, we estimated and compared streamflow mean transit times (MTT) with potential explanatory hydro-geomorphological and climate variables. Using a simple lumped convolution integral model with a Gamma distribution as transfer function (best-fit Kling Gupta efficiencies up to 0.92), our tropical dataset resulted in short MTTs from 49 to 497 days (0.13 – 1.4 years), together with considerable presence of new water in the stream and low damping ratios in most of the catchments. The gamma distribution alpha parameter was below the previously identified quasi-global pattern of around 0.5 in 5 out of 7 catchments. Principal Component Analysis (PCA) and a relative importance test identified rock type (%), days with zero precipitation and the water storage capacity as the most important controls on TT. In addition, the TT distribution as indicated by the Gamma distribution alpha parameter was best explained by annual evapotranspiration, altitude, and Andosol soil cover (%). Our findings identified the key controls on TT and TT distribution in fast-responding tropical catchments compared to other geomorphic and climate zones, emphasizing the value of TT as a coherent descriptor that can be used for catchment characterization.

Coupled Electrical – Thermal – Electrochemical Model of a Battery Module

A battery module comprises of several lithium-ion cells connected in series and parallel configuration to obtain the desired voltage, current and power specifications. The overall response of a module can be affected by (i) the electrical topology, (ii) the thermal topology and (iii) the cell-to-cell variations. The distribution of current depends on the series/parallel assembly and variation in interconnect resistance in the module. Operation of a cell is accompanied by an increase in temperature. In a module, the thermal environment seen by a cell is different depending on whether it is an interior cell or a cell at the boundary of module exposed to environment. There is additional thermal cross talk between cells through heat conduction in metallic interconnects. Finally, there can be several reasons for cell-to-cell variation in a module. The cells used for building a module can have variable state of charge and internal resistance at the manufacturing level. As the module is cycled, the ageing of cells in a module can differ due to variation in current, evolution of range of lithiation of electrodes and the temperature of the cell.In this research work, we develop a coupled electrical, thermal, and electrochemical model to simulate the charge and discharge of a battery module with the overall aim of identifying the cell with largest performance degradation and most likelihood of failure. This physics-based modeling approach comprises of a simplified electrochemical and lumped thermal model of an individual cell. At the module level, the modeling framework is extended to include the electrical and thermal connectivity along with the electrochemical response.

Semi-batch and batch low-salt-rejection reverse osmosis for brine concentration

Brine management strategies require efficient methods of desalinating high-salinity streams (> 7 wt%). Low-salt-rejection reverse osmosis (LSRRO) provides salt leakage to reduce the trans-membrane osmotic pressure, and has higher water recovery than reverse osmosis (RO). However, LSRRO has high energy consumption (e.g., >5kWh/m3 for seawater feed). In this work, we develop novel transient multistage processes (i.e., semi-batch and batch) that employ LSRRO membranes to desalinate high-saline streams. Herein, we use a simplified lumped model to capture the system performance under ideal and non-ideal conditions and optimize salt rejection per pass for the multistage system. The results show that the batch LSRRO system performs dewatering with fewer stages and more efficiently than the steady-state LSRRO. In particular, the multistage batch system significantly outperforms the steady-state LSRRO by reducing energy consumption between 38 % to 73 %. The ZLD application for 4-stage batch systems requires energy consumption between 1.07 and 6.96kWh/m3 for the feed salinity range between 0.1 and 1 mol/L. Conversely, semi-batch LSRRO is less efficient than steady-state and batch LSRRO. It is constrained by the loss due to the mixing of streams which results in more stages, tighter range for membrane selectivity, and higher energy consumption than batch LSRRO.

Microwave Switch Architecture for Superconducting Integrated Circuits Using Magnetic Field-Tunable Josephson Junctions

We report on the design, fabrication, and measurement of a low-temperature microwave switch architecture that can be fully integrated on chip using single Josephson junctions and superconducting bias lines. The basic switching element used is a reflective single-pole-single-throw switch that is realized by tuning the critical current of a single Josephson junction by way of a local flux bias. A single-pole-single-throw switch is demonstrated at 4.2 K to have an on/off ratio in excess of 20 dB up to 12 GHz. This element is then incorporated into the design of a single-pole-double-throw switch that exhibits an on/off ratio above 20 dB up to 10 GHz. The switches require no intrinsic power dissipation in either state, and their performance was verified for input powers of -100 dBm to -60 dBm. S-parameter simulations using a simple lumped element model are in good agreement with the experimental data, allowing for the design to be extended to larger switch architectures.

Development of simple semi-distributed approaches for modelling complex rainfall–runoff process

ABSTRACT The semi-distributed approaches proposed in the past for simulating rainfall–runoff (RR) still require extensive hydro-meteorological data for their complex calibration process. Therefore, research efforts are needed to develop novel and innovative semi-distributed RR models that require a minimum amount of data and effort. In this study, four semi-distributed RR models are proposed using a simple lumped model in a distributed sense by gradually enforcing spatial distribution in terms of hydro-meteorological and physiographical features in a basin. Only rainfall, runoff, and temperature data from three contrasting basins were employed in developing the proposed models. The results show that semi-distributed models performed better than the lumped model, and the accuracy increased with gradual enforcement of the spatial variations in various data. Further, the results suggest that incorporation of the basin’s physiographic features is the most important aspect in developing efficient semi-distributed RR models followed by hydrological and climatic information in a basin.

A Markov chain Monte Carlo analysis of carbon-phenolic ablation through a lumped physical model

Payloads and other rocket components use Thermal Protection Systems (TPS) to avoid the effects of high heat fluxes generated by aerodynamic heating or propellant burning. The most used type of TPS is the ablative thermal shield, employing polymeric composite ablators. Ablative and thermophysical properties of such materials must be known for TPS design. These properties are often difficult to access experimentally, and vary according to the manufacturing process, ratio between reinforcement and matrix and the fiber direction in the case of composites, and other process variables. Inverse solution methods were initially applied in computational models to solve the heat transfer problems in space vehicles. This work proposes an inverse methodology, using the Markov chain Monte Carlo (MCMC) method, to determine the ablative properties of carbon-phenolic materials manufactured by biased tape wrapping, starting from arc-jet ablation results of samples of this material. A simplified but robust lumped physical model is used to represent the direct problem. The obtained values of these properties were used in the direct problem in a more refined mesh, and the simulation was compared to the experiments. Good agreement between numerical and experimental data was obtained, allowing the use of this methodology in estimation of ablation properties.

A Drift-Diffusion Based Modeling and Optimization Framework for Nanoscale Spin-Orbit Torque Devices

We present a comprehensive set of experimentally validated/calibrated models that capture the physics of the nanoscale spin-orbit torque (SOT) devices. We consider various effects that are prominent at nanoscale including incomplete current redistribution, interface spin mixing, and nonuniform resistivity that were ignored in the prior modeling efforts. We develop a formalism based on drift-diffusion equations and the transfer matrix method to accurately estimate spin current distribution. We utilize finite element simulations to accurately calculate electric current density and field, and see considerable differences to the results from the simplified lumped model commonly used. For example, we calculate ~20% smaller spin current in a 15-nm-wide ferromagnet with a 4-nm-thick <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> -W SOT channel. We further account for the effect of interface scattering on resistivity. Finally, we quantify the optimal SOT-layer thickness that minimizes the write energy as a function of spin diffusion length and conductivity of SOT materials. We show that the optimal thickness increases with the spin diffusion length and decreases with the conductivity.

Seismic assessment and finite element modeling of traditional vs innovative point fixed glass facade systems (PFGFS)

In the last decades, recent earthquakes have further highlighted the high vulnerability of non-structural components. Post-earthquake damage due to building envelope, equipment and building contents can lead to substantial economic losses in terms of repair costs and daily activity interruption (downtime). Moreover, non-structural damage can represent a life-safety threat for both occupants and pedestrians. These considerations confirm the crucial need for developing low-damage systems for either structural or non-structural elements. This paper aims to assess the seismic performance of glazed facade systems, widely adopted in modern buildings, focusing on point fixed glass facade systems (PFGFSs), also referred to as “spider glazing”. In this work, a numerical investigation is developed to study the seismic performance of such systems at both local-connection level through a 3D FEM in ABAQUS as well as at global system level through a simplified lumped plasticity model in SAP 2000 to assess the overall in-plane capacity of the facade. Based on the local connection and global facade system behavior, a novel low-damage connection system is herein proposed, and a parametric study is carried out on the key parameters influencing the facade capacity. The benefits of implementing low-damage connection details are highlighted by an increase of the in-plane capacity of the facade system when compared to a traditional solution. To further investigate the potential of the proposed low-damage details in preserving the integrity of the facade system itself, non-linear time history analyses have been carried out on a case-study building equipped with the innovative PFGFSs.

Numerical simulation of the general rate model of chromatography using orthogonal collocation

Process chromatography is a critical manufacturing step in the purification of biopharmaceutical therapeutics and monoclonal Antibody (mAb) capture using Protein A-chromatography is the most expensive step in the entire production chain. Protein A-chromatography performance is hard to predict due to variations in chromatography column characteristics causing wastage and reduced efficiency. Additionally, it is not yet established how to use Protein A-chromatography optimally in continuous manufacturing. Mechanistic modeling of the chromatography process enables simulation-based optimization of operations to both reduce waste and increase productivity in continuous manufacturing. We present an easy-to-use, yet computationally efficient Python package called Simulation Testbed for Liquid Chromatography (STLC). STLC is a chromatography simulator implementing a solver for the General rate model, a comprehensive mathematical model in the field, and the simplified Lumped kinetic model. STLC uses orthogonal collocation to discretize the spatial domain turning the equations into an algebraic system of ordinary differential equations. The equations are integrated in time with a fixed step length backward Euler method. We evaluate STLC in numerical trials and benchmark against high-resolution references showing high-order convergence. This allows for reduced computation system size making the package a good choice for use in the rapid prototyping of simulated chromatography processes.

Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models

• We test stochastic processes to improve modeling of uncertainty in a real case study. • Bayesian inference and cross-validation are used to calibrate and assess performances. • Results highlight clear benefits for appropriate modeling choices. • We make recommendations to uncover/avoid issues due to overparameterization. • We test a novel parallel framework that simplifies access to HPC resources. The traditional description of a hydrological system with a deterministic, conceptual model and a lumped output error term does not explicitly consider the main mechanisms of uncertainty generation due to approximate process representation, unobserved variability in processes and influence factors, and input uncertainty. In this study, we test the description of such intrinsic uncertainty in conceptual models by making process rates stochastic through stochastic, time-dependent rate parameters. We analyze the advantages and challenges of this approach by using Bayesian inference to jointly estimate model parameters, parameters of the stochastic processes, and the time series of the stochastic parameters. Numerically, we use a particle filter to infer the stochastic time series and to approximate the marginal likelihood for Markov chain sampling of the constant parameters. Compared to the lumped error formulation, we achieve a more realistic description of uncertainty, as we obtain larger errors in intrinsic states, larger uncertainty during prediction than calibration periods (a feature missing for simple lumped error models), and autocorrelated model outputs. However, the additional degrees of freedom introduced with stochastic parameters can lead to an unintentional compensation for model deficits or input errors. This problem is symptomatic of model structure inadequacy or poor selection of the parameters that are made stochastic, and can be diagnosed through cross-validation and careful posterior analysis. The proposed approach is computationally more demanding and its implementation more challenging than the traditional description of hydrological systems using a deterministic model with a lumped error term. However, its advantages both in providing a more realistic representation of uncertainties and in diagnosing model deficiencies suggest its adoption and further development in future studies.

Multidegree-of-Freedom State-Space Modeling of Nonlinear Pull-in Dynamics of an Electrostatic MEMS Microphone

Capacitive micromachined ultrasound transducers (CMUTs) are most frequently used to generate ultrasound by superimposing the stimulus waveform and a steady bias voltage. This results in the best signal linearity, but limits the maximum displacement to which the diaphragm can be driven. Operating in the collapse-snapback excitation mode involves applying a voltage larger than the electrostatic pull-in threshold, and allows the diaphragm to traverse the entire depth of the air gap. Modeling the dynamics of the pull-in process is complicated by the inherent nonlinearity of the electrostatic transduction, nonlinearity of viscous damping with respect to the diaphragm displacement, and coupling between the electrical, mechanical, and acoustical domains. We have developed a multi-degree-of-freedom numerical model, using lumped elements to discretize the mechanical diaphragm and acoustic components. Simple one-dimensional lumped element models fail to accurately account for the varying contact between diaphragm and backplate, and the change in effective diaphragm area over the course of the cycle. Our discretized model is in excellent agreement with LDV measurements made on a commercially-developed MEMS microphone in air, and shows promise for using collapse-snapback mode as a means of generating impulsive ultrasound signals in air. [2021-0216]

Hybrid model-based online estimation of air temperature in mobile small-scale cooling chambers

Mobile, small-scale refrigeration applications for last-mile deliveries have gained increased importance in recent years. As they face disturbances and frequent door openings more extensively than long-distance transport, reliable temperature information is crucial for control concepts to comply with temperature regulations and increase efficiency. For desired ruggedness, sensors are typically integrated within the cooling unit, yielding substantial deviations between actual air temperature in the cooling chamber and measured one — particularly in periods of altered airflow conditions resulting from fan switching and the actual door opening status. This article introduces and compares two hybrid, online estimation procedures to overcome this issue: firstly, a Kalman-filter approach based on a simple lumped physical heat transfer model, and secondly, a gray-box-model approach resulting from a realizable inversion of the physical model. Experimental investigations of typical operating profiles provide 14 h of real-world data to parameterize (11.75 h data length), validate (2.25 h data length), and compare both estimators. The proposed concepts are based on a sensor setup available in state-of-the-art system architectures and provide satisfactory temperature estimates with more than 83 % overall fit. As the algorithms provide comprehensive process insight independent of the actual operating condition, sophisticated control schemes can be built upon the concept. • Hybrid, model-based estimation approaches for air temperature in refrigerated trucks. • Kalman-filter approach based on physically motivated heat transfer model. • Gray-box-model approach resulting from realizable inversion of the physical model. • Experimental data drive parametrization, validation, and performance comparison. • Easy-to-implement algorithms offer reliable process insight for control concepts.

Numerical Modelling of Traditional Buildings Composed of Timber Frames and Masonry Walls under Seismic Loading

ABSTRACT Existing heritage buildings are often composed of diverse materials and structural typologies, representing a challenge for structural analysis tasks. This work investigates the combined use of simple Lumped Plasticity Models (LPM) and macro-mechanical Finite Element (FE) approaches to evaluate the seismic response of structures composed of timber frames and masonry walls. The calibration of these engineering models is derived from a wide set of nonlinear static analyses reproducing benchmark experiments on timber and masonry specimens. The LPM and FE models are used eventually to appraise the seismic response of two existing timber-masonry hybrid buildings, located in the historical centre of Valparaíso, Chile. The nonlinear analyses performed with these models predict the acceleration-displacement capacity of the buildings under seismic-like horizontal loading, revealing their potential local and global failure mechanisms.

Full-Wave Methodology to Compute the Spontaneous Emission Rate of a Transmon Qubit

The spontaneous emission rate (SER) is an important figure of merit for any quantum bit (qubit), as it can play a significant role in the control and decoherence of the qubit. As a result, accurately characterizing the SER for practical devices is an important step in the design of quantum information processing devices. Here, we specifically focus on the experimentally popular platform of a transmon qubit, which is a kind of superconducting circuit qubit. Despite the importance of understanding the SER of these qubits, it is often determined using approximate circuit models or is inferred from measurements on a fabricated device. To improve the accuracy of predictions in the design process, it is better to use full-wave numerical methods that can make a minimal number of approximations in the description of practical systems. In this work, we show how this can be done with a recently developed field-based description of transmon qubits coupled to an electromagnetic environment. We validate our model by computing the SER for devices similar to those found in the literature that have been well-characterized experimentally. We further cross-validate our results by comparing them to simplified lumped element circuit and transmission line models as appropriate.

SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models

Abstract. Catchment-scale hydrological models are widely used to represent and improve our understanding of hydrological processes and to support operational water resource management. Conceptual models, which approximate catchment dynamics using relatively simple storage and routing elements, offer an attractive compromise in terms of predictive accuracy, computational demands, and amenability to interpretation. This paper introduces SuperflexPy, an open-source Python framework implementing the SUPERFLEX principles (Fenicia et al., 2011) for building conceptual hydrological models from generic components, with a high degree of control over all aspects of model specification. SuperflexPy can be used to build models of a wide range of spatial complexity, ranging from simple lumped models (e.g., a reservoir) to spatially distributed configurations (e.g., nested sub-catchments), with the ability to customize all individual model components. SuperflexPy is a Python package, enabling modelers to exploit the full potential of the framework without the need for separate software installations and making it easier to use and interface with existing Python code for model deployment. This paper presents the general architecture of SuperflexPy, discusses the software design and implementation choices, and illustrates its usage to build conceptual models of varying degrees of complexity. The illustration includes the usage of existing SuperflexPy model elements, as well as their extension to implement new functionality. Comprehensive documentation is available online and provided as a Supplement to this paper. SuperflexPy is available as open-source code and can be used by the hydrological community to investigate improved process representations for model comparison and for operational work.

A Multi-Fidelity Model for Simulations and Sensitivity Analysis of Piezoelectric Inkjet Printheads.

The ink drop generation process in piezoelectric droplet-on-demand devices is a complex multiphysics process. A fully resolved simulation of such a system involves a coupled fluid–structure interaction approach employing both computational fluid dynamics (CFD) and computational structural mechanics (CSM) models; thus, it is computationally expensive for engineering design and analysis. In this work, a simplified lumped element model (LEM) is proposed for the simulation of piezoelectric inkjet printheads using the analogy of equivalent electrical circuits. The model’s parameters are computed from three-dimensional fluid and structural simulations, taking into account the detailed geometrical features of the inkjet printhead. Inherently, this multifidelity LEM approach is much faster in simulations of the whole inkjet printhead, while it ably captures fundamental electro-mechanical coupling effects. The approach is validated with experimental data for an existing commercial inkjet printhead with good agreement in droplet speed prediction and frequency responses. The sensitivity analysis of droplet generation conducted for the variation of ink channel geometrical parameters shows the importance of different design variables on the performance of inkjet printheads. It further illustrates the effectiveness of the proposed approach in practical engineering usage.

Electromagnetic Scattering by Networks of High-Permittivity Thin Wires

The electromagnetic scattering from interconnections of high-permittivity dielectric thin wires with sizes smaller than (or almost equal to) the operating wavelength is investigated. A simple lumped element model for the polarization current intensities induced in the wires is proposed. The circuit elements are capacitances and inductances between the wires. An analytical expression for the induced polarization currents in terms of the magneto-quasistatic current modes is obtained. The connection between the spectral properties of the loop inductance matrix and the network's resonances is established. The number of the allowed current modes and resonances is deduced from the topology of the circuit's digraph. The coupling to radiation is also included, and the radiative frequency shifts and the quality factors are derived. The introduced concept and methods may find applications both at the microwaves and in nanophotonics.

Exhalatory dynamic interactions between patients connected to a shared ventilation device.

In this work a shared pressure-controlled ventilation device for two patients is considered. By the use of different valves incorporated to the circuit, the device enables the restriction of possible cross contamination and the individualization of tidal volumes, driving pressures, and positive end expiratory pressure PEEP. Possible interactions in the expiratory dynamics of different pairs of patients are evaluated in terms of the characteristic exhalatory times. These characteristic times can not be easily established using simple linear lumped element models. For this purpose, a 1D model using the Hydraulic and Mechanical libraries in Matlab Simulink was developed. In this sense, experiments accompany this study to validate the model and characterize the different valves of the circuit. Our results show that connecting two patients in parallel to a ventilator always resulted in delays of time during the exhalation. The size of this effect depends on different parameters associated with the patients, the circuit and the ventilator. The dynamics of the exhalation of both patients is determined by the ratios between patients exhalatory resistances, compliances, driving pressures and PEEPs. Adverse effects on exhalations became less noticeable when respiratory parameters of both patients were similar, flow resistances of valves added to the circuit were negligible, and when the ventilator exhalatory valve resistance was also negligible. The asymmetries of driving pressures, compliances or resistances exacerbated the possibility of auto-PEEP and the increase in relaxation times became greater in one patient than in the other. In contrast, exhalatory dynamics were less sensitive to the ratio of PEEP imposed to the patients.

Impact of COMPASS-U vacuum vessel and the first wall structures on signals of in-vessel magnetic diagnostic coils

The paper evaluates the impact of metallic structures of the COMPASS-U tokamak design on signals measured by in-vessel magnetic diagnostic coils. The eddy current shielding caused by the tokamak conductive structures of the vacuum vessel and plasma facing components is evaluated using finite element analysis performed by ANSYS Maxwell software. The simulation of the sudden shifts in the radial or vertical position of the plasma column returns 33–45% amplification of the tangential field component that from the most part would be analogous to a simple lumped circuit model approximation, despite the complex 3D shape of the nearby plasma facing components. The simulation of a rotating helical filament close to plasma edge (approximating a rotating magnetic island magnetohydrodynamic (MHD) structure) reveals an unexpected spatial modulation of the magnitude attenuation coefficient of up to 45% for the tangential field component across different positions relative to the PFC holders. Both results have led to the described conclusions for the sensor positioning design, specifically to the decision to install plasma position feedback sensors in between the robust holders of the PFC tiles, and the plasma MHD activity sensors strictly symmetrically with respect to these PFC structures.