Lumped Model Research Articles

Stochastic approach for modeling soft fingers with creep behavior

Soft robots have high adaptability and safety due to their softness and are therefore widely used in human society. However, the controllability of soft robots to perform dexterous behaviors is insufficient when considering soft robots as alternative laborers for humans. Model-based control methods are effective for achieving dexterous behaviors. To build a suitable control model, problems based on specific properties, such as creep behavior and variable motions, must be addressed. In this paper, a lumped parameterized model for soft fingers with viscoelastic joints is established to address creep behavior. The parameters are expressed as distributions, which allows the model to account for motion variability. Furthermore, stochastic analyzes are performed based on the parameter distributions. The model results are consistent with the experimental results, and the model enables the investigation of the effects of various parameters related to robot variability.

Improving the interpretability and predictive power of hydrological models: Applications for daily streamflow in managed and unmanaged catchments

In recent years, Machine Learning (ML) techniques have gained the attention of the hydrological community for their better predictive skills. Specifically, ML models are widely applied for streamflow predictions. However, limited interpretability in the ML models indicates space for improvement. Leveraging domain knowledge from conceptual models can aid in overcoming interpretability issues in ML models. Here, we have developed the Physics Informed Machine Learning (PIML) model at daily timestep, which accounts for memory in the hydrological processes and provides an interpretable model structure. We demonstrated three model cases, including lumped model and semi-distributed model structures with and without reservoir. We evaluate the first two model structures on three catchments in India, and the applicability of the third model structure is shown on the two United States catchments. Also, we compared the result of the PIML model with the conceptual model (SIMHYD), which is used as the parent model to derive contextual cues. Our results show that the PIML model outperforms simple ML model in target variable (streamflow) prediction and SIMHYD model in predicting target variable and intermediate variables (for example, evapotranspiration, reservoir storage) while being mindful of physical constraints. The water balance and runoff coefficient analysis reveals that the PIML model provides physically consistent outputs. The PIML modeling approach can make a conceptual model more modular such that it can be applied irrespective of the region for which it is developed. The successful application of PIML in different climatic as well as geographical regions shows its generalizability.

Textile-based quad-band electromagnetic absorber design for wearable applications

In this article, a textile-based quad-band electromagnetic absorber (TQA) is presented for wearable applications in the S-band frequency region. The proposed TQA consists of two asymmetric X-shaped resonators (AXRs) with different arm lengths placed on fully grounded denim fabric. Since each arm of the two AXRs excites a different resonance mode, four distinctive absorption bands can be achieved by adjusting the arm lengths. The proposed structure with optimal design parameters, designed and optimized using CST Microwave Studio Suite v.2021, provides over 0.99 absorption peaks at 2.68, 2.80, 3.00, and 3.18 GHz frequencies in the simulation environment. Also, an efficient lumped equivalent circuit model is extracted for the absorber to demonstrate the principle of the quad-band operation in the respective frequencies. In addition, a good agreement between simulated and measured results is observed and thus the numerical design is validated. More importantly, to the best of the authors’ knowledge, this is the first textile based absorber design that provides absorbance in four different frequency bands.

Control of chaotic vibrations in lumped mass models of the vocal folds

Lumped mass models have been widely used as low-dimensional systems to better understand the physics underlying human phonation. This is a highly non-linear process in which subglottal flow emanating from the lungs excite self-oscillations of the vocal folds. Consequently, a pulsating volume velocity is established that produces acoustic waves, which then travel through the vocal tract and are released from the mouth as voice. The self-oscillations of the vocal folds may be affected by many undesirable factors like the presence of polyps, lateral paralyses, excessive subglottal pressure, etc., and transition from regular to chaotic motion. This gives rise to abnormal phonation. In this work, we explore the theoretical possibility of adding smart materials to vocal fold lumped mass models. The smart material must be such that its damping can be dynamically modified. By proper tuning, one can establish a feedback control mechanism that restores chaotic vocal fold oscillations to normality. This would constitute the essence of a pacemaker for phonation.

Modeling and simulation of microwave assisted catalytic pyrolysis system of waste plastics polymer for fuel production

Pyrolysis is a promising method of chemically recycling plastic waste, as it allows for the recovery of both energy and materials. In this work, a comprehensive mathematical model has been developed to predict the pyrolysis of plastic wastes over ZSM-5 catalyst in microwave-assisted pyrolysis (MAP) system for fuel production. To conduct a transient numerical analysis of the underlying processes, a lumped kinetic model that takes into account three lumped pyrolysis products (olefins, paraffins, and aromatics) is coupled with the equations that govern the microwave field, heat transfer, mass transfer, and fluid flow (Darcy's law). The distributions of electric field, temperature, and pyrolysis products within MAP are presented. The study investigated the effects of several factors on the rate of production and consumption in the pyrolysis reactions of a waste plastic mixture when using MAP. These factors include the microwave power input, the inlet velocity of the fluidizing gas, as well as the mass and particle size of the catalyst used. Increasing the input power leads to a higher intensity of the electric field, which causes a greater increase in temperature within the same time frame. The mass and particle size of the catalyst used also have a significant impact on the yield of olefins, paraffins, and aromatics. Reducing the particle size of the catalyst generally increases the reaction rate, but particle sizes smaller than 50 μm are not ideal for fluidization due to increased intermolecular forces. Increasing the inlet velocity of the fluidizing gas may result in an incomplete consumption of intermediates and a low yield of products. All in all, The MAP system is a highly efficient and effective design for using plastic waste as a source of energy, due to its superior energy efficiency and lower processing temperature compared to traditional fluidized-bed reactors.

Effect of thermal gradients on inhomogeneous degradation in lithium-ion batteries

Understanding lithium-ion battery degradation is critical to unlocking their full potential. Poor understanding leads to reduced energy and power density due to over-engineering, or conversely to increased safety risks and failure rates. Thermal management is necessary for all large battery packs, yet experimental studies have shown that the effect of thermal management on degradation is not understood sufficiently. Here we investigated the effect of thermal gradients on inhomogeneous degradation using a validated three-dimensional electro-thermal-degradation model. We have reproduced the effect of thermal gradients on degradation by running a distributed model over hundreds of cycles within hours and reproduced the positive feedback mechanism responsible for the accelerated rate of degradation. Thermal gradients of just 3 °C within the active region of a cell produced sufficient positive feedback to accelerate battery degradation by 300%. Here we show that the effects of inhomogeneous temperature and currents on degradation cannot and should not be ignored. Most attempts to reproduce realistic cell level degradation based upon a lumped model (i.e. no thermal gradients) have suffered from significant overfitting, leading to incorrect conclusions on the rate of degradation.

Fast Meshless Solution With Lumped Friction for Laminar Fluid Transients

Abstract Fluid transients without friction in pipelines can be solved by a time-domain exact solution, using a simple recursive process without computational grid. However, the calculation time cost of this approach is very high because of the recursion algorithm. Its improved method, named as the fast meshless solution (FMS), was developed to speed up the computation by introducing time-line interpolation. However, when the friction is considered, the conventional distributed friction model cannot be employed directly for the FMS is meshless. To address this problem, the fluid friction is lumped at pipe ends, and both steady and unsteady laminar flow are investigated. Three kinds of lumped models are proposed here, and compared with a numerical case of the water hammer. The laminar fluid transients can be calculated quickly by the present method, with a little reduced accuracy. This method may be of interest in a quick assessment of the piping fluid transients.

Comprehensive uncertainty analysis for surface water and groundwater projections under climate change based on a lumped geo-hydrological model

Sustainable management of aquifers requires long-term predictions of their aquifer-scale groundwater balance under climate change with meaningfully quantified uncertainty. In our analysis, we account for uncertainty in model parameters, measured data, model errors, stochastic model inputs (e.g., rainfall, potential evapotranspiration), and climate scenarios. To afford this analysis, we rely on an extension of lumped hydrological models that includes groundwater flow and storage, called lumped geohydrological model (LGhM). It shows good model performance and is three orders of magnitude faster than 2D or 3D numerical groundwater models. We use Markov chain Monte Carlo (MCMC) for Bayesian inference on a calibration period to quantify posterior parameter uncertainty and lumped data-and-model error. Then, we perform Monte Carlo forward runs with stochastic weather inputs under three different climate scenarios to quantify uncertainty in long-term predictions up to the year 2040. We apply our approach on a virtual reality representation of the Wairau Plain aquifer, New Zealand. We hypothesize that the variability in future climate is the most important impact factor. To test this hypothesis, we disentangle the overall uncertainty between data/model, parameters, weather, and climate inputs. We expect our approach to be highly useful for arbitrary types of catchments because the LGhM model structure can easily be adapted.

Runoff retention characteristics of forested and deforested catchments: an analysis using a spatially lumped model

ABSTRACT This study investigates the runoff characteristics of forested and deforested catchments using the Soil Conservation Services–curve number (SCS-CN) model from the perspective of the Kerala floods in 2018 and 2019. The forested and deforested catchments chosen for the study are the drainage area of the Kakkayam Dam and Punoor River respectively of Kozhikode District, Kerala. The study used input variables such as rainfall, land use/land cover (LU/LC) and soil data to estimate the runoff depth from these catchments during the floods in 2018 and 2019 using the SCS-CN model. Here, the hydrological response of these catchments is examined by different scenarios of rainfall and LU/LC change. It is found that the deforested catchment generates more runoff compared to the forested catchment under identical rainfall conditions. However, the study shows that, the runoff depth in the deforested catchment is expected to reduce if certain portion of plantations and barren land converts into the forest cover. The ability of runoff retention of the forested catchment is expected to lose if the forest-covered land is utilized for the plantation activities.

Nonlinear modeling of magnetic materials for circuit simulations

Magnetic materials in the form of magnetic rings are widely used in power engineering products. In many cases, they operate in high frequency and in nonlinear conditions, e.g., as damping elements in electrical power substations equipped with Gas-Insulated Switchgear (GIS) where they provide suppression of Very Fast Transient Overvoltages (VFTOs). To model phenomena in GIS with magnetic rings it is required to have realistic time-dependent models of magnetic materials operating in a wide frequency range and nonlinear conditions. Nowadays, this has become even more relevant due to the actual trend in the industry to create digital twins of physical devices. Models composed of high-precise discrete lumped nonlinear elements are in demand in circuit simulators like SPICE. This work introduces a method based on classical algorithms that find equivalent lumped models of magnetic cores based on frequency-dependent measurements of impedance under DC-bias current. The model is specifically designed to have smooth behavior in the current domain and thanks to that to improve numerical stability in the time domain simulations.

An effective modelling approach for multi-body dynamic analysis of epicyclic gear train of GTF considering both structural flexibility and mechanical interactions

In this paper, a new modelling approach is proposed for the dynamic investigation of epicyclic gear train, and the novelty of this work lies in consideration of both structural flexibility and mechanical interactions during the analysis procedure. The method is of capacity to directly present the dynamic results of the supporting structure for convenient practical engineering evaluation and reduce the dimension of the system reasonably with appropriate assumptions for better computational efficiency. Firstly, the mechanical interactions among components are discussed in detail, and the principle that the structural flexibility works is also explained at length. Secondly, taking the epicyclic gear train of the geared turbofan (GTF) engine; for example, the dynamic model of the system is then established based on the developed hybrid user-defined elements. For model validation, the governing equations of the system are also derived by the lumped mass method. Thirdly, with the same values of the parameters, the results of normal dynamic meshing force obtained by the proposed model are compared with the ones by the lumped mass model. It can be stated from the data that (1) the maximum relative error between the theoretical value and the average value calculated by the two models is 8.28%, (2) the gear mesh frequency obtained by the two models are sufficiently close to the theoretical value, and (3) the fluctuation trends of the dynamic force keep basically consistent with each other. In summary, the comparison presented clearly indicates that the proposed model is indeed reasonable, which provides a new way for dynamic investigation and structural redesign of a large epicyclic gear train. Finally, as a practical engineering application, the vibration result of the deformable supporting structure of the GTF gear train is also presented, which directly provides valuable reference for vibration monitoring, fault diagnosis and other engineering problems in practice.

Lumped Plasticity Model and Hysteretic Performance of Ultra-High-Performance Concrete Rocking Pier.

Rocking piers using ultra-high-performance concrete (UHPC) have high damage-control capacity and self-centering characteristics that can limit the post-earthquake recovery time of bridges. To study the hysteretic behavior of UHPC rocking piers, a lumped plasticity model is proposed that comprises two parallel rotational springs and which can accurately calculate their force-displacement hysteretic behavior. Three states of the rocking piers, decompression, yield, and large deformation, are considered in this study. The model is verified based on existing experimental results, and the hysteretic characteristics of the UHPC rocking piers, such as strength, stiffness, and energy dissipation, are further analyzed. The research results show that the lumped plasticity analysis model proposed in this study can predict the force-displacement hysteretic behavior of the rocking piers accurately. Moreover, the hysteretic performance of the UHPC rocking piers is better than that of rocking piers using normal-strength concrete. An increase in the energy dissipation reinforcement ratio, pre-stressed tendon ratio, and initial pre-stress improves the lateral stiffness and strength of the UHPC rocking piers. However, the increase in the pre-stressed tendon ratio and initial pre-stress reduces their energy-dissipation capacity.

Zero-Pole Optimization of a Novel High-Quality-Factor Planar Helical Resonator

A novel micro-solenoid resonator has been designed, simulated, and measured. The solenoid core consisted of a DuroidTM circuit board with a relative permittivity of 2.2. The resonator design incorporated four embedded copper vias with a radius of 125 µm and three surface conductors to form a rectangular coil. A pitch size of 250 µm was used for a 3.02 mm thick substrate. To enhance the resonator’s performance at higher frequencies, a capacitance was introduced in series through the via. This additional capacitor effectively couples the inductance, resistance, and stray capacitance. The optimization of the quality factor was investigated through pole transfer analysis, resulting in an increased resonance frequency of 12.25 GHz and an elevated Q-factor of 306. Moreover, besides its very high Q-factor, this resonator offers a simplified design and easy integration. An analytical lumped circuit model was employed to investigate the design, and the measured S-parameters closely matched the analytical model and electromagnetic simulation results. The tuned resonator exhibited a superior quality factor compared to other micro-resonators.

Feasibility study on person identification utilizing frequency response functions of human fingers

A novel biometric recognition method is presented for future personal devices, utilizing the frequency responses of the human body, especially the fingers, for personal identification. A series of experimental vibration modal analyses were conducted to measure the frequency response functions (FRFs) of individuals’ fingers. In addition, a biodynamic lumped system model was constructed for the major components of a finger, including phalanges, joints, and skin. Analytical FRFs were then computed for a comparative study with the measured FRFs. In the person identification process, we employed an effective feature extraction method based on the correlation coefficient between frequency bins of the measured FRFs to extract the most effective set of frequency bins from the entire FRF spectrum. These extracted features were utilized to train a support vector machine for classifying individuals. In a controlled experimental setup, the classification results showed a maximum accuracy of 99%, affirming the feasibility of using the vibration responses of human fingers as a novel biometric method for person recognition.

Enhanced prediction of the decongealing performance of aero-engine oil coolers with various fin types and operating conditions using lumped model

Freezing of the flight environment of an aircraft occasionally causes the congealing of oil in the oil coolers. Although decongealing tests and re-designs require longer durations, many studies have examined the cooling loss arising from this phenomenon. Numerical simulations for the decongealing process are computationally expensive, and experiments under typical operating scenarios are costly. In this paper, an efficient one-dimensional flow and thermal approach is proposed, with transient simulations under realistic decongealing scenarios involving a standard fuel cooled oil cooler. With the objective function being the maximization of the heat transfer and minimization of the pressure drop, different cooler configurations with various internal fins were examined for both design and off-design conditions. The proposed lumped model provides a similar accuracy with a lower calculation cost compared to an earlier model. It also ensures better stability and easier code modifications. The current study demonstrates an optimum heat transfer and pressure drop with improved total decongealing performance when offset-strip fins on both the oil and fuel sides (ΔP: 23.9 psi, Tout: 12.3 °C) or an offset-strip fin on the oil side and a wavy or pin fin on the fuel sides (ΔP: 34.2 psi, Tout: 11.4 °C) are applied.

Co-Hydroprocessing of Fossil Middle Distillate and Bio-Derived Durene-Rich Heavy Ends under Hydrotreating Conditions

Methanol-to-gasoline (MTG) and dimethyl ether-to-gasoline (DTG), as industrially approved processes for producing greenhouse gas-neutral gasoline, yield byproducts rich in heavy mono-ring aromatics such as 1,2,4,5-tetramethylbenzene (durene). Due to its tendency to crystallize and the overall poor fuel performance, the heavy fuel fraction is usually further processed using after-treatment units designed for this purpose. This research article discusses the co-hydroprocessing (HP) of bio-derived heavy gasoline (HG) with fossil middle distillate (MD), drawing on available refinery hydrotreaters. Co-HP experiments were conducted in a laboratory-scale fixed bed reactor using an industrial CoMo/γ-Al2O3 catalyst, varying the space-time between 0.7 and 4.0 cmCat3 h cmFeed−3 and the reaction temperature between 340 and 390 °C. In addition to the durene conversion, special attention was paid to the octane and cetane numbers (CN) of gasoline and MD, respectively. A six-lump model with ten parameters was developed to predict relevant fuel yields dependent on the process conditions. Under stable catalyst conditions, C10 aromatic conversions of more than 60% were obtained, while the CN remained close to that of pure MD. Harsh process conditions increased the gasoline yield up to 20% at the cost of MD, while the kerosene yield remained almost constant. With an optimized lumping model, fuel yields could be predicted with an R2 of 0.998. In this study, co-HP heavy aromatic-rich MTG/DTG fuels with fossil MD were proven to be a promising process strategy compared to a stand-alone after-treatment.

Physics-informed neural networks to solve lumped kinetic model for chromatography process

Numerical method is widely used for solving the mechanistic models of chromatography process, but it is time-consuming and hard to response in real-time. Physics-informed neural network (PINN) as an emerging technology combines the structure of neural network with physics laws, and is getting noticed for solving physics problems with a balanced accuracy and calculation speed. In this research, a proof-of-concept study was carried out to apply PINN to chromatography process simulation. The PINN model structure was designed for the lumped kinetic model (LKM) with all LKM parameters. The PINN structure, training data and model complexity were optimized, and an optimal mode was obtained by adopting an in-series structure with a nonuniform training data set focusing on the breakthrough transition region. A PINN for LKM (LKM-PINN) consisting of four neural networks, 12 layers and 606 neurons was then used for the simulation of breakthrough curves of chromatography processes. The LKM parameters were estimated with two breakthrough curves and used to infer the breakthrough curves at different residence times, loading concentrations and column sizes. The results were comparable to that obtained with numerical methods. With the same raw data and constraints, the average fitting error for LKM-PINN model was 0.075, which was 0.081 for numerical method. With the same initial guess, the LKM-PINN model took 160 s to complete the fitting, while the numerical method took 7 to 72 min, depending on the fitting settings. The fitting speed of LKM-PINN model was further improved to 30 s with random initial guess. Thus, the LKM-PINN model developed in this study is capable to be applied to real-time simulation for digital twin.

Preventing thermal runaway propagation in lithium-ion batteries: Model-based optimization of interstitial heat-absorbing thermal barriers

Advances in cathode and anode materials enable the energy density of lithium-ion batteries to increase further. However, safety concerns, particularly regarding thermal runaway propagation (TP), are intensifying. TP is a cascading reaction that occurs when a cell undergoing thermal runaway in a module triggers adjacent cells, leading to module destruction. Preventing TP is crucial, especially in applications like electric vehicles. This research introduces a method for designing safe battery systems using an interstitial barrier with a heat-absorbing effect to avert TP. For this purpose, a lumped element model parameterized by different methods is implemented to simulate the cell-to-cell TP inside a battery module. Comparison with TP tests on 3-cell modules of varying barrier thicknesses validates the model. The results exhibit effective TP prevention by the barrier, with TP occurring in just 41s without it. Moreover, our model is able to predict the TP times from the experiments. Further, this work demonstrates a design strategy involving a barrier with optimal thickness for maintaining volumetric energy density while ensuring safety. Therefore, this work highlights the significance of a heat-absorbing barrier and demonstrates its optimal module integration using a validated simulation model to promote the development of safe batteries.

Photoacoustic based evaluation of viscoelastic properties of Gram-negative and Gram-positive bacterial colonies

Mechanical properties of bacterial colonies are crucial considering both addressing their pathogenic effects and exploring their potential applications. Viscoelasticity is a key mechanical property with major impacts on the cell shapes and functions, which reflects the information about the cell envelope constituents. Hereby, we have proposed the application of photoacoustic viscoelasticity (PAVE) for studying the rheological properties of bacterial colonies. In this regard, we employed an intensity-modulated laser beam as the excitation source followed by the phase delay measurement between the generated PA signal and the reference for the characterization of colonies of two different types of Gram-positive and Gram-negative bacteria. The results of our study show that the colony of Staphylococcus aureus as Gram-positive bacteria has a significantly higher viscoelasticity ratio compared to that value for Acinetobacter baumannii as Gram-negative bacteria (77% difference). This may be due to the differing cell envelope structure between the two species, but we cannot rule out effects of biofilm formation in the colonies. Furthermore, a lumped model has been provided for the mechanical properties of bacterial colonies.

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.