Dynamic Model Research Articles

Energy forecast for a cogeneration system using dynamic factor models

Cogeneration is used in different sectors of industry and it allows that two types of energy to be efficiently obtained from a single source. Accurate predictions are fundamental to optimize energy production, considering the variability that occurs in the daily market. This study adjusts and predicts cogeneration using real data from a Spanish energy technology center, using dynamic factor analysis methodology and incorporating covariates such as temperature and relative humidity. A comparative analysis is performed to evaluate the improvements achieved by implementing cluster-structured dynamic models versus other methods. Furthermore, a robust interpolation method has been implemented to handle missing data in both the main variable and the covariates.

Ensemble Predictability of Week 3/4 Precipitation and Temperature over the United States via Cluster Analysis of the Large-Scale Circulation

Abstract Forecasting the week 3/4 period presents many challenges, resulting in a need for improvements to forecast skill. At this distance from initial conditions, numerical models struggle to present skillful forecasts of temperature, precipitation, and associated extremes. One approach to address this is to utilize more predictable large-scale circulation regimes to make forecasts of temperature and precipitation anomalies, using the association between the regimes and surface weather obtained from reanalysis products. This study explores the utility of k-means cluster analysis on geopotential heights and their ability to make skillful regime predictions in the week 3/4 period. Using 14-day running means of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) 500-hPa geopotential heights for the wintertime December–February (DJF) period, circulation regimes are identified using k-means clustering. Each period is assigned a cluster number, allowing the compositing of any reanalysis or observation variable to form cluster maps. Maps of 500-hPa height, 2-m temperature, precipitation, and storm-track anomalies are some of the variables composited. The utility of these relationships in a dynamical forecast setting is tested via Global Ensemble Forecast System v12 (GEFSv12) hindcasts and real-time ensemble suite forecasts. Week 3/4 deterministic and probabilistic experimental forecasts are then derived from cluster assignments using several methods. We find, via a conditional skill analysis, forecasts strongly correlated with a cluster exhibit greater skill for both dynamical model and cluster-derived forecasts. Our preliminary results represent a step forward to aid forecasters make more skillful assessments of the circulation regime and its associated surface weather for this challenging forecast time scale. Significance Statement Our paper links the local statistics of 14-day precipitation and temperature within the United States to very broad preferred patterns of winds and pressure over the wide Pacific–North American region. Such patterns, known as “circulation regimes,” provide the background that heavily influences local surface conditions. We find that forecasts for which midatmospheric anomalies are closely aligned with one or more circulation regimes are better at predicting the U.S. weather probabilities than other week 3–4 forecasts. A tool based on this finding identifies forecasts for which confidence is higher. Future work will be designed to further exploit the links between circulation regimes and weather to improve the accuracy of week 3–4 forecasts.

Gasification of mixed plastic-biomass pellets in an updraft fixed bed reactor: a simplified dynamic model

In the context of materials recycling, updraft gasifiers are promising small and middle-scale reactors to obtain building blocks and/or energy from waste plastic and biomasses. To this aim, these kinds of materials can also be mixed and reduced into pellets, while the needed heat enters the process with a heated carrier gas. In order to preliminarily design a gasifier to check its feasibility with an available feedstock, currently available models are inadequate. Thermodynamic ones are useless for the purposes of sizing, while too detailed rate-based models (e.g. based on fluid-dynamic modelling) are too substrate specific, need detailed input data and are extremely time consuming. A dynamic model of a fixed-bed reactor for biomass gasification is presented here. The gasifier is loaded continuously from the top with solid pellets and fed with counter-current air flow. The model considers: i) a one-step gasification kinetics, yielding a product spectrum which matches experimental data from the literature; ii) dynamic gas and solid energy balances and iii) steady-state energy balance for the furnace. The model has been applied to describe a tubular furnace (Ø 40 cm) which gasifies 500 – 1000 kg day-1 of mixed wastes using air heated up to 1200 °C: on the basis of the produced chemicals, the energy consumption was estimated as ca. 2 MJ per kg of solid feedstock. This simplified approach proved robust in describing the overall yields and start-up dynamics, showing higher reliability than equilibrium models in addressing the temperature profiles, at the cost of a simplified reaction kinetic and pellet description with respect to more complex simulation models. The model validation was done by comparison between the calculations results and available pilot-plant data. An overall good fit of the data can be concluded. The solid-gas heat transfer and the bed packing are the main computational criticalities to achieve a reliable process description.

A Compartmental Mathematical Model of Novel Coronavirus-19 Transmission Dynamics

A Compartmental Mathematical Model of Novel Coronavirus-19 Transmission Dynamics

Transient Dynamics of a Porous Sphere in a Linear Fluid

This article describes the unsteady translational motion of a porous sphere with slip-surface in a quiescent viscous fluid. Apart from its radius a and density ρs , the particle is characterized by its permeability parameter γ , slip-length l and effective viscosity-ratio ϵ for interior flow. The Reynolds number for the system is assumed to be small leading to negligible convective contribution, though the transient inertia for both the liquid and the solid is comparable to viscous forces. The resulting linearized but unsteady flow-equations for both inside and outside the porous domain are solved in time-invariant frequency domain by satisfying appropriate boundary conditions. The analysis ultimately renders frequency-dependent hydrodynamic friction for the suspended body. The frictional coefficient is computed under both low and high frequency limit for different values of γ, l and ϵ so that the findings can be compared to known results with impermeable surface. Moreover, the parametric exploration shows that the sphere acts like a no-slip body even with non-zero l if aγ ≫ 1/√ϵ . Scaling arguments from a novel boundary layer theory for flow inside porous media near interfaces explain this rather unexpected observation. Also, computed fluid resistance is incorporated in equation of motion for the particle to determine its time-dependent velocity response to a force impulse. This transient response shows wide variability with ρs, γ, l and ϵ insinuating the significance of the presented study. Consequently, the paper concludes that slip and permeability should be viewed as crucial features of submicron particles if unexpected variability is to be explained in nano-scale phenomena like nano-fluidic heat conduction or viral transmission. Thus, the theory and findings in this paper will be immensely useful in modeling of nano-particle dynamics.

Dual-functional adsorptive membranes for PFAS removal: Mechanism, CFD simulation, and selective enrichment

The remediation of emerging water contaminants, particularly per- and polyfluoroalkyl substances (PFAS), presents challenges due to their refractory nature and the presence of competing substances. Dual-functional adsorptive membranes, with hydrophobic backbone and quaternary ammonium moieties, were thereby designed to selectively intercept organic competitors while enrich PFAS. A 96.8 % removal of perfluorooctanoic acid (PFOA) was achieved and this effective removal (>90 %) maintained across five reuse cycles with a total treatment capacity of 650 L m−2. Rather than the rejection mechanism of nanofiltration process, these adsorptive membranes utilize synergistic electrostatic attraction and hydrophobic interactions, leading to a greater enrichment factor of 18.5 (PFOA over humic acid) and a permeability of 34.6 L m-2h−1 bar−1 (1.9- and 4.5-fold higher than reported NF 270 membranes, respectively). Furthermore, computational fluid dynamics (CFD) modeling revealed that the sponge-like matrix effectively prevents channeling flow and enhance access to adsorption sites. Sensitivity analysis and the high Damkohler number indicated that the adsorption process is mass transfer-controlled, with the key parameters ranked in order of significance: residence time > fluid viscosity > intrinsic adsorption rate. With consistent removal performance with co-existing competitors, efficient regeneration, and reusability, the dual-functional adsorptive membranes offer promising practical efficacy for PFAS remediation.

Adaptive control of plug-in hybrid electric vehicles based on energy management strategy and dynamic programming algorithm

This study mainly analyses the fuel consumption of plug-in hybrid vehicles during operation. A new control method for automobiles based on energy management strategy and dynamic programming algorithm is proposed. The new method plans and analyses the minimum electricity consumption, and then uses dynamic programming algorithms to analyse this parameter. The research results indicated that the vehicle state was constantly changing with the variation of SOC value during driving. The energy mobilization of the vehicle was more obvious after adding dynamic programming strategy. The efficiency of the vehicle was relatively high in driving state 1, with a minimum value of 70%, which was about 20% higher than in driving state 4. The average fuel consumption in driving state 2 was 1.8L higher than in other driving states. The overall efficiency of automobiles after incorporating dynamic programming was improved, with a shorter time to reach the lowest efficiency point compared with not incorporating dynamic programming algorithms. The highest efficiency value was 7.86% higher than that of not incorporating dynamic programming models. The new control method can reduce energy consumption and improve the energy management and control effect. The study provides a better research direction for energy management and control of hybrid electric vehicles in the future.

Dynamic Hysteresis Model of GO Silicon Steel Considering Skin Effect and Saturation Effect

Dynamic Hysteresis Model of GO Silicon Steel Considering Skin Effect and Saturation Effect

Influence of the stratification parameters on the wake field of an underwater vehicle in a two-layer stratified flow

Because the ocean exhibits different stratification states in different seasons and regions, the effect of different stratification parameters on a submarine wake must be studied. In particular, to investigate such effect in a two-layer stratified flow, this study established a computational fluid dynamics (CFD) model based on the URANS equations, shear-stress transport (SST) k-ω turbulence model, and Eulerian multiphase flow model. The volume of fluid (VOF) method was adopted to implement the free-surface capture method. The working conditions of the SUBOFF model under an infinite diving depth and near the free surface were compared with those of the experiments, and the convergence of the time step and grid number under stratified flow conditions was verified. These validation steps proved the feasibility of the CFD method. Finally, the effects of the stratification parameters on the free surface waves, internal waves, and turbulent kinetic energy behind the vehicle were observed by varying the stratification parameters to achieve different working conditions. The results show that when an underwater vehicle sails in a two-layer stratified flow, the interstratified density ratio and depth of the internal wave surface affect its wake field. When the underwater vehicle sails in the water layer, with an increase in the interstratified density ratio, the free-surface roughness increases and the turbulent kinetic energy decreases. When the underwater vehicle sails in the salt water layer, the result is just the opposite.

Dynamic Fleet Configuration Model for Optimizing Earthmoving Operations Using Mixed Integer Linear Programming

Dynamic Fleet Configuration Model for Optimizing Earthmoving Operations Using Mixed Integer Linear Programming

Parameter instabilities and monetary policy in a small open economy: Evidence from an estimated model for the UK

This paper reconsiders whether monetary policy in small open economies responds to exchange rates by studying possible parameter instabilities in a Dynamic Stochastic General Equilibrium model. The main focus of the paper is to revisit preceding evidence on the response to exchange rate movements by the Bank of England and determine if its reaction function has remained constant throughout the sample. To this end, I estimate a small open economy general equilibrium model using Bayesian econometric techniques over rolling windows. I find overwhelming evidence of shifts in several parameters, including those related to the policy rule. Furthermore, posterior odds tests reveal a time-varying response to exchange-rate fluctuations by the monetary authorities. The results favor the model with the nominal exchange rate embedded in the policy rule for the initial subsamples. However, the evidence steadily evolves across windows and ultimately changes to prefer the model specification with no exchange rate. The paper also documents evident variations in the model dynamics derived from the instability of parameters via rolling-window impulse response functions and variance decomposition analysis.

Vocs pollution and respiratory exposure in commercial and residential underground parking garages

The indoor air quality in Underground Parking Garages (UPGs) has deteriorated significantly, primarily due to the high concentrations of particulate matter and volatile organic compounds (VOCs) emitted by idling or low-speed motor vehicles. However, the compositional characteristics and respiratory exposure to VOCs in UPGs have not been quantitatively analyzed. To establish a method for investigating the respiratory exposure to VOCs among different populations in UPGs, a three-dimensional dynamic diffusion model of indoor pollutants was developed based on monitoring data from 116 components in various UPGs in a large city in northern China. The results indicated that air pollution in underground spaces poses significant health risks to workers and children. Furthermore, a comprehensive approach is essential for improving ventilation capacity and air quality in underground transportation spaces.

The role of government integrity in the impact of environmental taxes on comparative advantage in environmental goods and climate change in emerging markets

The goal of this study is to examine how environmental taxes influence the comparative advantage in environmental products and carbon emissions within emerging economies. To gain a better understanding, we examine whether this impact changes depending on the level of government integrity. This study utilizes panel autoregressive distributed lag (ARDL) techniques and a two-step generalized method of moments (GMM) dynamic panel model to ensure accuracy. The results indicate that increased environmental taxes mitigate the comparative advantage in environmental goods for emerging markets. However, for countries with high levels of government integrity, higher environmental taxes enhance their competitive edge in environmental goods. Additionally, our findings show that although a rise in environmental taxes is associated with higher carbon emissions, raising such taxes results in a reduction in carbon emissions for emerging economies with solid government integrity. These findings suggest that robust political institutions are crucial in promoting the comparative advantage of emerging markets in environmental goods and mitigating climate change. In the absence of substantial confidence in political or governmental institutions, the efficient implementation of climate taxes poses considerable challenges. Furthermore, we observe that an increase in the comparative advantage of environmental goods results in a decrease in carbon emissions.

Source term estimation in the unsteady flow with dynamic mode decomposition

When estimating source parameters in the unsteady flow, the flow information of pollution dispersion is indispensable. It is common practice to save the flow information in the computer in advance but it requires large storage space. Besides, when contaminants are released after a time period of the flow field saved before, calculating the flow field by Computational Fluid Dynamics (CFD) model demands massive computational cost. Dynamic Mode Decomposition (DMD) is thereby proposed to solve the problems mentioned above. Firstly, the fields are decomposed by DMD. Then, the simulated concentrations are acquired by the adjoint equation based on the field synthesized by DMD. Finally, the measured concentrations and the simulated concentrations are taken into Bayesian inference to accomplish source term estimation (STE). The results show that the estimated results with high accuracy are obtained both in the reconstruction stage and in the prediction stage when using the fields obtained by DMD. Also, the efficiency of predicting the future flow by DMD is much higher than that by CFD simulation, suggesting that DMD can improve the efficiency of STE in some cases. As DMD uses a small number of dominant modes to synthesize the approximate fields with minor errors, it reduces the storage demand of flow information in STE. The sampling range and sampling resolution should be properly selected to ensure the accuracy of STE.

Break a peg! A study of stablecoin co-instability

Following the increasing adoption of stablecoins, their robustness has become an ongoing concern for investors and regulators alike. This article studies the co-instability of a large panel of stablecoins by identifying their structural breaks and co-occurrences. Moreover, we use Dynamic Time Warping (DTW) and Dynamic Conditional Correlation DCC-GARCH models to assess spillover effects in the wake of four major black swan events in the crypto world. Similar to prior literature, we conclude that algorithmic stablecoins were the major shock receivers of the IRON TITAN and TERRA LUNA crashes, highlighting the importance of allowing for sufficient margins of safety in their design. We also observe that the FTX bankruptcy and the Silicon Valley Bank collapse had repercussions of a different nature and affected more categories of stablecoins, from algorithmic to fiat money-backed. We also highlight how, irrespective of the idiosyncratic or systemic nature of the shocks, well-known custodial stablecoins, as well as the most successful crypto-collateralized tokens, showed resilience during or in the immediate aftermath of these events.

Short-Circuit Dynamic Model of SiC MOSFET Considering Failure Modes

Short-Circuit Dynamic Model of SiC MOSFET Considering Failure Modes

Assessment of a coupled electricity and hydrogen sector in the Texas energy system in 2050

Due to its ability to reduce emissions in the hard-to-abate sectors, hydrogen is expected to play a significant role in future energy systems. This study modifies a sector-coupled dynamic modeling framework for electricity and hydrogen by including policy constraints, carbon prices, and possible hydrogen pathways and applies it to Texas in 2050. The impact of financial policies, including the US clean hydrogen production tax credit, on required infrastructure and costs are explored. Due to low natural gas prices, financial levers are necessary to promote low-carbon hydrogen production as the optimized solution. The Levelized Costs of Hydrogen are found to be $1.50/kg in the base case (primarily via steam methane reformation production) and lie between $2.10 - 3.10/kg when production is via renewable electrolysis. The supporting infrastructure required to supply those volumes of renewable hydrogen is immense. The hydrogen tax credit was found to be enough to drive production via electrolysis.

Simplified assessment of structures with clutching inertia-friction systems by equivalent linearization methods

The innovative Clutching Inertia System (CIS), has garnered increasing recognition for its effectiveness in mitigating structural vibrations. To enhance the efficiency of passive CIS, introducing suitable energy dissipation mechanisms for the rotation inertia component is imperative. This study delves into the dynamic behavior of CIS, augmented with additional friction damping. Initially, the influence of supplementary friction damping within the CIS framework is examined through a dynamic model of a Single-Degree-of-Freedom (SDOF) system, integrated with the CIS and incorporating the Coulomb friction model. Subsequently, to streamline the dynamic analysis of the CIS and optimize the friction force thereby enhancing control efficiency while minimizing inactive durations, the paper introduces two distinct Equivalent Linearization Methods (ELMs). Furthermore, an assessment of the CIS’s dynamic performance, subjected to various external excitations, is presented. The findings highlight the crucial role of supplemental friction damping in reducing the inactivity of CIS and enhancing its overall control effectiveness. The employed ELMs demonstrate commendable accuracy and practicality for both response assessment and CIS performance optimization. In essence, the CIS, when integrated with supplemental friction damping, exhibits superior performance in suppressing structural displacement responses across diverse excitations, particularly in longer-period structures. Conversely, a more pronounced efficacy in managing structural acceleration responses is observed in structures with shorter periods. The study concludes that for specific structural applications, enhancing supplemental friction damping is more advantageous for vibration control than increasing the CIS’s inertia.

Data-Assisted Dynamic Modeling of Bionic Robotic Fish and Its Precise Speed Control

Data-Assisted Dynamic Modeling of Bionic Robotic Fish and Its Precise Speed Control

Hydrogen-fueled PFI SI engine investigation for near-zero NOx emissions in de-throttled and supercharged ultra-lean burn conditions

This study investigates the efficiency and combustion characteristics of a hydrogen port fuel injection (PFI) spark ignition (SI) engine under various load levels, excess air ratios and intake pressures. Experiments were conducted on a single-cylinder research engine to evaluate the effects of throttle opening and supercharging on pumping work and combustion parameters. The key findings indicate that abnormal combustion events are more closely related to the relative air-fuel ratio (λ) than to load, further limiting load increases during de-throttled operation. Additionally, combustion variability compromised mixture enleanment in both naturally aspirated and supercharged conditions. The gross indicated efficiency was approximately 40.7% across the range of 2.2 < λ < 3.5 with minimal variation. Efficiency gains were linked to reduced heat transfer losses in lean conditions, as validated by computational heat transfer, thermodynamic and fluid dynamic models on Gamma Technologies GT-ISE software. Moreover, nitrogen oxides (NOx) emissions were nearly zero for all test conditions when λ was above 2.2. These findings provide crucial insights into optimizing hydrogen engine performance under various intake pressures, highlighting the potential for achieving high efficiency and low emissions.