Rigorous Model Research Articles

Multi-Station Hydrological Modelling to Assess Groundwater Recharge of a Vast Semi-Arid Basin Considering the Problem of Lack of Data: A Case Study in Seybouse Basin, Algeria

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data.

Three-dimensional transient heat transfer analysis of micro-plasma arc welding process using volumetric heat source models

Abstract The micro plasma arc welding process is associated with different physical phenomena simultaneously. This results in complexities to comprehend the actual mechanism involved during the process. Therefore, a robust numerical model that can compute the weld pool shape, temperature distribution, and thermal history needs to be addressed. Unlike, other arc welding processes, the micro plasma arc welding process utilizes thin sheets of thickness between 0.5 and 2 mm. However, joining thin sheets using a high-density arc welding process quickens the welding defects such as burn-through, thermal stresses, and welding-induced distortions. The incorporation of a surface heat source model for computational modeling of the high energy density welding process impedes heat transfer analysis. In that respect, researchers have developed numerous volumetric heat source models to examine the welding process holistically. Although, selecting volumetric heat source models for miniature welding is a significant task. The present work emphasis developing a rigorous yet efficient model to evaluate weld pool shape, temperature distribution, and thermal history of plasma arc welded Ti6Al4V sheets. The computational modeling is performed using a commercially available COMSOL Multiphysics 5.4 package with a finite element approach. Two different prominent thermal models, namely, Parabolic Gaussian and Conical power energy distribution models are used. A comparative analysis is carried out to determine the most suitable heat source model for evaluating temperature distribution, peak temperature, and thermal history. The analysis is done by juxtaposing the simulated half-cross-section weld macrographs with the published experimental results from independent literature. The numerical results showed that the proximity of top bead width magnitude was obtained using the Parabolic Gaussian heat source model for low heat input magnitude of 47.52 and high heat input magnitude of 65.47 J·mm−1, respectively. In terms of percentage error, the maximum top bead width percentage error for the Parabolic heat source model is 13.26%. However, the maximum top bead width percentage error for the Conical heat source model is 18.36%. Likewise, the maximum bottom bead width percentage error for the Parabolic heat source model and the Conical heat source model is 12.3 and 25.8%, respectively. Overall, it was observed that the Parabolic heat source model produces the least deviating outcomes when compared with the Conical distribution. It was assessed that the Parabolic Gaussian heat source model can be a viable heat source model for numerically evaluating micro-plasma arc welded Ti6Al4V alloy of thin sheets.

A survey on optimization-based approaches to Dynamic Centralized Group Key management

Abstract—In secure multicast communication, only authorized group members are able to receive the transmitted data. Key generation, distribution, and management are all carried out by a single entity (called the Key Server) in the centralized system. The main challenges of a dynamic centralized group key management scheme include scalability overhead, rekeying overhead, storage overhead, maintaining forward and backward secrecy, etc. Logical Key Hierarchy (LKH), one of the key management methods, uses a tree structure to manage keys to share with participants. Due to the fact that members may join or exit the group at any time during communication, a crucial problem in centralized group key management (CGKM) is minimizing rekeying costs while maintaining a balanced tree. The majority of CGKM methods effectively update the group key by modifying cryptographic techniques or based on logical/heuristic arguments. One of the efficient approaches is based on an optimization model with the two mentioned important objectives. In this paper, we conduct a survey on optimization-based approaches to dynamic CGKM, which can be divided into two categories based on logical/heuristic arguments and a rigorous mathematical optimization model.

Advanced Dual-Band Antenna for Optimised Vehicular Communication Systems

The advancement of Intelligent Transportation Systems (ITS) has rendered the development of robust communication networks critical. Within the realm of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) exchanges, this necessity becomes even more pronounced. Addressing this pivotal requirement, our study details the design and realisation of a sophisticated dual-frequency antenna system. Utilising the cutting-edge Advanced Design System (ADS) software, the design targets efficacious support for V2V and V2I communications across separate frequency bands, thus mitigating interference and enhancing data throughput, crucial for uninterrupted connectivity. Through rigorous simulations, modelling, iterative optimisation, and meticulous prototyping, the design is actualised. Preliminary testing demonstrated the antenna’s superior performance in gain, bandwidth, and radiation patterns within the designated frequencies. These performance indicators are essential for reliable communication in dynamic vehicular environments. As vehicles evolve towards greater intelligence, the demand for powerful communicative instruments, such as this antenna, becomes unequivocal. The proposed design not only promises improved network connectivity but also fosters advancements in road safety and traffic efficiency. This investigation lays the groundwork for setting benchmarks in future vehicular antenna communications, articulating the benefits of the proposed system and charting a course for subsequent technological breakthroughs. The ultimate objective remains to hone this design for seamless incorporation into diverse automotive systems. Summarily, the paper presents an intersection of innovation and practical application, casting light on the prospective trajectory of V2V and V2I communications.

Scale-Dependent Generalized Thermoelastic Damping in Vibrations of Small-Sized Rectangular Plate Resonators by Considering Three-Dimensional Heat Conduction

Given that thermoelastic damping (TED) is one of the main causes of energy dissipation in miniaturized structures, calculation of its exact amount is of particular importance in the design of such elements. Considering three-dimensional (3D) heat transfer along with the scale effect on both mechanical and thermal areas is one of the decisive factors in the more rigorous modeling of TED in small-sized resonators. This paper exploits the modified couple stress theory (MCST) and dual-phase-lag (DPL) heat conduction model to establish an analytical TED relation for rectangular micro/nanoplate resonators with 3D heat conduction. At the start, the non-Fourier heat equation corresponding to 3D DPL model is derived. Then, the solution of temperature distribution is determined by employing infinite trigonometric series. Moreover, the scale-dependent frequency of the system is presented in the context of MCST. Eventually, with the help of entropy generation (EG) method, an analytical TED expression considering 3D heat conduction is established. The precision of the presented solution is examined by comparing it with a simpler model available in the literature. By choosing two common types of boundary conditions, i.e. fully-clamped (CCCC) and fully-simply (SSSS) supported plates, the influence of various factors on TED changes is comprehensively investigated in simulation section. According to the outcomes, in plates with a lower ratio of length and width to thickness, the dimension considered for heat conduction model has a noticeable impact on the variations of TED.

Integrated process design and self-optimizing control: A probabilistic approach

This work introduces a probabilistic-based integrated process design and self-optimizing control approach grounded in a steady-state model, aiming to strike a balance between solution reliability and optimality. The proposed approach offers a practical and cost-effective solution by considering disturbances as random variables with known probability distribution functions. To propagate these disturbances to process outputs, the unscented transform method is utilized alongside rigorous first-principles process models. Additionally, probability levels are assigned to process constraints based on user-defined specifications, providing flexibility to tailor the design to desired risk confidence levels. The effectiveness and benefits of the approach are demonstrated through an application on an extractive distillation process with pre-concentration.

Simple model for water wash performance in amine scrubbing for CO2 capture

In amine-based capture systems, a water wash is necessary to remove gaseous amine to minimize atmospheric emissions and maximize amine recovery. Water wash simulation requires rigorous thermodynamic and kinetic models like those for absorption and stripping systems. An offline water wash model has been developed based on simplified thermodynamic and mass transfer assumptions to simulate a single-stage water wash for flue gas from gas-fired turbines with little or no aerosol, and to expedite simulations without needing to utilize process modeling software. Calculation of activity coefficients using both Pitzer–Debye–Hückel and Debye–Hückel theory suggest that the liquid phase in a typical water wash will be ideal due to the dilute concentration of molecular and ionic species.Vapor phase piperazine (PZ) is predicted with a driving force based on the volatility of the free amine that has not reacted with other species or dissociated into its ionic form, and the predicted outlet concentration is nearly identical to that predicted by rigorous Aspen PlusⓇ simulations. The predicted UT FEED outlet concentration is 220 ppb compared to 260 ppb predicted by Aspen PlusⓇ.Single-stage water washes are predicted to have single ppm concentration of MEA leaving the wash outlet flue gas. Amino-methyl-propanol (AMP) is predicted to be reduced to 10–30 ppm by a single-stage wash, and is predicted to be a difficult-to-capture amine without further washing steps. This prediction correlates with published TCM data from an ALIGN-CCUS campaign. Amine compounds at a similar or lower volatility to that of PZ are predicted to be reduced to ppb levels via a single-stage wash.

Estimating the line packing time for pipelines transporting carbon dioxide

During the operation of pressurised pipelines transporting compressible fluids, line packing is employed as an effective method that uses the pipeline itself as a buffer storage, compensating for fluctuations in the fluid supply or demand. While in large-capacity natural gas transmission systems, reaching maximum operating pressures during line packing is usually not of practical concern, in small capacity pipelines transporting low-compressibility fluids, such as liquid or dense-phase CO2, line packing can occur quickly, and therefore, estimating the line packing times becomes important to ensure avoiding exceeding the pipeline maximum allowable operating pressure. In this study, a correlation for estimating the line packing time is derived from the transient mass balance in the pipeline. The proposed correlation accounts for the pipeline overall dimensions, operating pressure and temperature, and the fluid properties, namely density and the expansion coefficient. The correlation is also adopted for the calculation of pipeline unpacking times caused by unbalanced discharge from a pipeline. A verification study on line packing in a dense-phase CO2 pipeline shows that within the ranges tested, the proposed correlation estimates conservatively the line packing times with ca. 15 % deviation from the results of simulations obtained using a rigorous transient pipeline flow model. The proposed correlation is also verified against predictions obtained using a parabolic flow model and is recommended for estimating line packing times for both dense-phase and gas-phase CO2 at pressures and temperatures in the ranges 2 - 12 MPa and 280 – 330 K, respectively. The limitations of the proposed line packing time correlation are discussed.

Numerical and theoretical analysis on soil arching effect of prefabricated piles as deep foundation pit supports

This study presents a detailed investigation into the soil arching effects within deep foundation pits (DFPs), focusing on their mechanical behavior and implications for structural design. Through rigorous 3D finite element modeling and parameter sensitivity analyses, the research explores the formation, geometric characteristics, and spatial distribution of soil arching phenomena. The investigation encompasses the influence of key parameters such as elastic modulus, cohesion, and internal friction angle on the soil arching effect. The findings reveal that soil arching within DFPs exhibits distinct spatial characteristics, with the prominent arch axis shifting as excavation depth progresses. Optimal soil arching is observed when the pile spacing approximates three times the pile diameter, enhancing soil retention and minimizing deformation risks. Sensitivity analyses highlight the significant impact of soil parameters on soil arching behavior, underscoring the critical role of cohesive forces and internal friction angles in shaping arching characteristics. By elucidating the interplay between soil parameters and soil arching effects, the research provides insights for optimizing pile spacing and structural stability.

Modeling and Analysis of Coupled Thermal and Mechanical Capacity Degradation in Silicon-Based Lithium-Ion Batteries

Large-format cells are gaining popularity for battery electric vehicles (BEVs) to maximize volumetric and gravimetric energy densities but are associated with challenges in ensuring adequate thermal management. Spatial current density and temperature variations negatively affect overall cell utilization and lifetime.In addition, the mechanical stresses generated within the silicon-based battery electrodes also cause aging and resultant capacity loss. The coupled effects of the thermal and mechanical factors could thus particularly exacerbate cell capacity degradation. Rigorous mechano-thermo-electrochemical models for battery degradation can be a powerful complementary tool to understand these phenomena better. Simulating performance scenarios can significantly improve cell design and experimentation while reducing time and cost commitments. Model-based design approaches thus have the potential to yield substantial economic benefits.This work shall serve as an extension to the previously developed thermal degradation model for non-uniform aging in lithium-ion batteries by coupling with mechanical models predicting the effects of volume change within the batteries over cycling. The observed capacity fade trend for a given battery is ultimately the result of an interplay between multiple degradation mechanisms, which depend on a range of design and operating parameters. The errors between the model predictions and experimental data can provide information on the suitability of a given model and the relative prevalence of a given degradation mechanism, with functional and practical benefits, as there exists significant variation in the parameters, mechanisms, and predictive capability of models in the literature. In addition, a rigorous model of volume changes increases the accuracy of predictions of dynamic stress-strain profiles, which in turn helps improve predictions of associated mechanical degradation phenomena. As a first step towards including mechanical effects, the current model builds on the previously reported studies for modeling volume change in porous electrodes due to intercalation (deintercalation) during lithiation (delithiation). This volume change leads to dimensional and porosity changes in the porous electrodes. Furthermore, these mechanical models will help predict generated stresses and strain profiles within the battery and will be related to models of resultant degradation, especially in the case of silicon/graphite electrodes characterized by substantial volume changes.

Endogenous Credit, Business Cycle, and Portfolio Selection

News story for “Endogenous Credit, Limited Commitment, Business Cycle” Countercyclical Investment Patterns with Endogenously Determined Credit Anticipated returns are sufficiently high to offset the elevated risks during downturns, presenting favorable investment opportunities. For instance, Warren Buffett accumulated more than $10 billion in profits amidst the 2008 financial crisis, as highlighted in his Wall Street Journal interview from October 2013: “In terms of simple profitability, an average investor could have performed just as well investing in the stock market if they bought during the panic period.” In “Endogenous Credit, Limited Commitment, Business Cycle,” Choi, Koo, Lim, and Yoo reveal a divergence in investment behavior between affluent and less affluent individuals during economic downturns. Whereas wealthier individuals tend to increase their exposure to risky investments, less affluent individuals tend to reduce theirs. We employ rigorous modeling and solution analysis to establish endogenous borrowing constraints in general equilibrium, elucidating the observed investment patterns.

A new method of the hydrocarbon secondary migration research: Numerical simulation

A three-dimensional invasion percolation simulation model is introduced and integrated into a novel three-dimensional geological modeling framework based on the “unit element” theory to study secondary hydrocarbon migration. Leveraging the computational efficiency inherent in the invasion percolation theory, the simulation method is effectively applied to basin-scale hydrocarbon migration using finely discretized grids. Sensitivity analysis demonstrates the substantial influence of geological parameters including structural configuration, sedimentary facies, and pressure, on simulation results. Noteworthy observations from this study encompass: (1) The intricate influence of sedimentary facies and petrophysical properties characteristics on hydrocarbon migration and accumulation patterns within structural and lithological traps. Favorable petrophysical attributes in the carrier beds enhance the likelihood of accumulation in the structural traps, while lithological traps are prevalent in less conducive carrier beds. (2) The significant impact of sand bodies exhibiting favorable petrophysical attributes, such as channels, on migration and accumulation profiles. This underscores the necessity of incorporating sedimentary facies and rock attributes into oil and gas resource exploration. (3) The pronounced effects of overpressure magnitude and direction on hydrocarbon migration and accumulation dynamics. (4) Optimal strategies for oil and gas resource exploration necessitate a comprehensive assessment of rock attributes, overpressure considerations, and sedimentary facies. The practical implementation of this methodology is demonstrated in an actual exploration project within China's Junggar Basin. The simulation results closely align with established oil recovery data and facilitate predictive identification of promising exploration areas. This indicates the methodology is applicable to all petroleum systems similar to Junggar Basin. Through practical applications, the development of a scientifically rigorous three-dimensional geological model for the study area, coupled with numerical simulations of oil and gas migration, facilitates the elucidation of accumulation patterns. This approach aids in identifying pivotal factors such as sand body distribution, internal structural composition, permeability attributes, and fracture behavior, which collectively influence oil and gas migration. Furthermore, by correlating insights obtained from oil and gas discoveries in wells, a deeper understanding of carrier bed properties and their geological evolution is attained.

Hybrid renewable energy source optimization using black widow optimization techniques with uncertainty constraints

To encourage the growth and use of renewable energy such as PV Solar Energy, Wind Energy, India is speeding up the creation of a renewable portfolio standard. Scheduling practises for thermal power and other renewable energy producers in the electric power system will shift as a result of the adoption of the standard and accompanying marketable green credits. In this study, we develop a dynamic economic emission dispatch model for wind, solar, and hydro power under tradable green certificates, taking into account many objectives simultaneously. The drive to transition towards cleaner and more sustainable energy sources has underscored the significance of optimizing hybrid renewable energy systems. This study presents a novel approach that leverages the Black Widow Optimization (BWO) algorithm to address the challenges of optimizing such systems while accounting for uncertainty constraints. The core problem revolves around the effective integration and management of multiple renewable energy sources, including solar, wind, and hydro, within a framework that ensures robustness and adaptability. In the face of variable weather conditions and equipment reliability uncertainties, the BWO algorithm excels in balancing exploration and exploitation to yield optimal solutions. Through rigorous modelling and sensitivity analysis, this study provides quantitative insights into the system's performance, offering a clear understanding of the trade-offs between cost-effectiveness and reliability. Real-world case studies validate the practicality of the proposed approach, underlining its importance in achieving sustainable and resilient energy systems. This study's goal is to minimise the yearly cost of operating a hybrid wind-solar renewable energy system to meet a specified load. The objective was to minimise the yearly cost of the system by selecting the optimal level of system components to meet the required load in an efficient and cost-effective manner. Several computational strategies inspired by nature, such as Black Widow Optimization (BWO), were used to maximise fitness. The fitness function and the techniques used to create it where both coded in MATLAB.

Improved marketing strategy of a hybrid renewable plant integrated with gravitational energy storage: Techno-economic analysis and multi-objective optimization

The intermittent nature of renewable energy sources, which could negatively impact the stability of the electricity grid and the economic viability of the technologies, has intensified concerns about their extensive contributions to the national energy systems' electricity supply. Energy storage systems have become increasingly relevant as a means for securing grids' stability with high shares of renewables. The purpose of this study is to investigate the potential of utility-scale gravitational energy storage as a ‘bidding strategy facilitator in the day-ahead market’ for renewable energy plants. With this ultimate goal, the size of the storage unit is not necessarily very large compared to the peak production capacity of the plant. This is in favor of the cost-effectiveness of the power plant due to today's unsupportive electricity pricing and market regulations for justifying large-scale energy storage systems. The gravitational energy storage system is assumed to accompany a PV farm in Denmark, just as a sample case study. The system is designed, sized, and planned for the optimal marketing strategy of the PV plant using rigorous techno-economic modeling and optimization techniques. According to preliminary findings, a 100 MWP PV plant with 5 MWh storage capacity can be built with a capital expenditure of $126.96 million, at a discounted payback period of 10.6 years, and reduced annual penalties of over 94.5 %.

Including CFD rigorous models in the optimal design of carbon capture plants through trust-region methods

Efficient technology alternatives are required to fulfill the environmental goals of reducing CO2 emissions at short and medium term. In this context, carbon capture using hollow fiber membrane contactors is an interesting alternative due to its operational flexibility, modularity, and high interfacial area. To elucidate the true potential of this technology, cutting-edge modeling and optimization techniques must be applied to improve key process performance indicators. In the present study, we develop a CFD rigorous model for a MEA-based absorber using membrane contactors. This model is included as an external function in the formulation of an optimization problem through the trust-region filter method, to minimize the CO2 avoided cost of the capture plant. As results, we obtain an optimal design with a CO2 avoided cost of 54.16 $/t-CO2 and a specific energy demand of 3.52GJ/t–CO2.

Fractional order viscoplastic modeling of anisotropically overconsolidated clays with modified isotach viscosity

Current overstress typed elastic viscoplastic models fall short in describing some time-dependent mechanical behaviors of anisotropically overconsolidated clays comprehensively. This paper presents a rigorous fractional order anisotropic elastic viscoplastic two-surface model for such clays, based on the principles of fractional consistency viscoplasticity and bounding or subloading surface theory. First, a three-dimensional formulation of isotach viscosity is proposed and integrated into two rate-dependent surfaces, i.e., the loading surface and yield surface. Then, by incorporating the stress-fractional operator of the rate-dependent loading surface into isotropic, progressive, and rotational hardening rules, the incremental form of stress-strain-time model with a fractional order viscoplastic flow rule is developed by meeting the consistency condition on the loading surface. Accordingly, the proposed model cannot only maintain the predictive capabilities of a classic bounding surface model but also describe the general features of the time-dependent behavior under various stress conditions. Validation and versatility of the proposed fractional order elastic viscoplastic model are successfully evaluated against constant strain-rate and stress relaxation tests on anisotropically overconsolidated resedimented Boston Blue clay.

Geomechanical investigation of casing collapse using finite element modeling: The role of cement sheath integrity

Casing collapse has been reported in several oil and gas wells all around the world. Cement sheath failure is one of the primary factors that may result in casing collapse. The growing focus on maintaining well integrity over the long term has prompted the creation of more detailed, realistic, and accurate models. Mechanical modeling of the casing-cement-formation setting can reveal the cement's capacity to withstand in-situ stresses, which is critical to sustaining the zonal isolation of the well throughout its lifetime. To date, the literature lacks a rigorous three-dimensional mechanical model to take into account all the geomechanical factors. This study aims to investigate the role of cement sheath failure in casing collapse by developing such a model. To do so, first, a three-dimensional numerical model was built in Abaqus using input data from a collapsed casing case study. Then, the required input data into the model were determined by following a step-by-step geomechanical procedure. Furthermore, to assess the model's accuracy and quality of the mesh, the numerical model was validated against an analytical model for stress distribution around the wellbore. As a preventive measure against casing collapse in upcoming infill wells, a new cement slurry was formulated, and its mechanical characteristics were measured through triaxial tests. The numerical results of the current wellbore cement and newly designed cement were compared to assess the effect of cement sheath integrity on casing collapse. The results revealed that the casing collapse in the case study can be highly attributed to the cement sheath shear failure and migration of the over-pressured formation fluid to the micro-annuli formed at the cement interfaces with the formation and the casing due to plastic deformation. The procedure outlined in this study can be used to design the wellbore cement according to the geomechanical factors to ensure well integrity.

Model-based techno–economic analysis of an integrated synthetic natural gas production system with direct air capture and water electrolysis

In this study, a techno-economic analysis is performed for an integrated system of carbon capture and utilization (CCU). The proposed system utilizes CO2 captured by a direct air capture (DAC) process using a metal–organic framework adsorbent. The captured CO2 is converted into a methane product, or synthetic natural gas (SNG), using hydrogen produced by water electrolysis. Rigorous mathematical models are used for the mass and energy balances in the major components of the proposed integrated system, allowing us to estimate the capital and operating costs and energy consumption. A sensitivity analysis is also performed to identify model parameters that significantly affect the SNG cost. Our analysis indicates that the thermal and electrical energies required to produce SNG are 0.409 MJ/Nm3-SNG and 19.6 kWh/Nm3-SNG, respectively, and the cost of SNG is within the range of 1.43–2.60 $/Nm3-SNG.

A complete physical 3D model from first principles of vibrational-powered electromagnetic generators

The dynamic behavior of a vibrational electromagnetic generator using a magnetic levitation architecture was theoretically and experimentally studied in great detail, when operating under a wide range of three-dimensional excitations. We developed a complete rigorous physical model from first principles based on the theory of electrodynamics of continua, centered on the laws of electrodynamics and balance of mass, linear momentum, angular momentum, energy and entropy. Local electromagnetic and gravitational body forces, couples and powers were considered, and the surface tractions were divided into constraint and friction components, as well as those due to external mechanical energy sources. The balance of linear momentum, angular momentum and circuit equations resulted in up to 13 non-linear differential equations describing the dynamics of the levitating-magnet and container, relating input forces and torques with output displacement, constraint forces and voltage. The balance of energy yielded a consistent equivalence between the time rate of change of the internal kinetic and potential energies of the generator and the output power, associated with the external circuit, Ohmic losses and friction losses, as well as the input mechanical power being supplied to the system by the environment. Both the input and output powers were proven to tend to increase equally when operating the generator under resonant conditions. The levitating generator was shown to be sensitive to axial translational and centrifugal inertial forces, each one effectively resulting in a uni-stable or bi-stable system. The dynamical response yielded multiple initial conditions dependent steady-states, hysteretic frequency output and chaotic characteristics. Relevant guidelines to optimize the energy conversion efficiency of energy harvesters are provided. This model was validated by experimental tests, including general 3D motions combining translations and rotations: cross-correlations exceeding 90% were achieved. Such Newtonian and Langrangian modelling approaches hold great potential to be easily adapted to a wide range of other electromagnetic generators, with multiple degrees-of-freedom and operating under various environments, such that significant advances in energy technologies can be supported.

New trends in modelling of breakthrough curves to remove pollutants using adsorption on advanced monoliths geometries

This work proposes a rigorous mathematical model capable of reproducing the adsorption process in dynamic regime on advanced monoliths geometries. For this, four bed geometries with axisymmetric distribution of channels and similar solid mass were proposed. In each geometry a different distribution of channels was suggested, maintaining constant the bed dimensions of 15 cm high and 5 cm radius. The mathematical modeling includes mass and momentum transfer phenomena, and it was solved with the COMSOL Multiphysics software using mass transfer parameters published in the literature. The overall performance of the column was evaluated in terms of breakthrough (CA/CA0 = 0.1) and saturation times (CA/CA0 = 0.9). The mass and velocity distributions obtained from the proposed model show good physical consistency with what is expected in real systems. In addition, the model proved to be easy to solve given the short convergence times required (2–4 h). Modifications were made to the bed geometry to achieve a better use of the adsorbent material which reached up to 80%. The proposed bed geometries allow obtaining different mixing distributions, in such a way that inside the bed a thinning of the boundary layer is caused, thus reducing diffusive effects at the adsorbent solid-fluid interface, given dissipation rates of about 323 × 10−11 m2/s3. The bed geometry composed of intersecting rings deployed the best performance in terms of usage of the material adsorbent, and acceptable hydrodynamical behavior inside the channels (maximum fluid velocity = 35.4 × 10−5 m/s and drop pressure = 0.19 Pa). Based on these results, it was found that it is possible to reduce diffusional effects and delimit the mass transfer zone inside the monoliths, thus increasing the efficiency of adsorbent fixed beds.