Dynamic Transfer Model Research Articles

Dynamic transfer model and applications of a penetrating projectile‐fuze multibody system

AbstractIn modern warfare, fortifications are being placed deeper underground and with increased mechanical strength, placing higher demands on the target speed of the penetrating munitions that attack them. In such practical scenarios, penetrating fuze inevitably experience extreme mechanical loads with long pulse durations and high shock strengths. Experimental results indicate that their shock accelerations can even exceed those of the projectile by several times. However, due to the unclear understanding of the dynamic transfer mechanism of the penetrating fuze system under such extreme mechanical conditions, there is still a lack of effective methods to accurately estimate and design protection against the impact loads on the penetrating fuze. This paper focuses on the dynamic response of penetrating munitions and fuzes under high impact, establishing a nonlinear dynamic transfer model for penetrating fuze systems, which can calculate the sensor overload signal of the fuze location. The results show that the relative error between the peak acceleration obtained by the proposed multibody dynamic transfer model and that obtained by experimental tests is only 15.7%, which is much lower than the 26.4% error between finite element simulations and experimental tests. The computational burden of the proposed method mainly lies in the parameter calibration process, which needs to be performed only once for a specific projectile‐fuze system. Once calibrated, the model can rapidly conduct parameter scanning simulations for the projectile mass, target plate strength, and impact velocity with an extremely low computational cost to obtain the response characteristics of the projectile‐fuze system under various operating conditions. This greatly facilitates the practical engineering design of penetrating ammunition fuze.

How dynamic transfer models can complement an equilibrium-based approach: Case studies of radiocesium transfer to forest trees following accidental atmospheric release

Accidental release of radionuclides caused by nuclear accidents like those in Fukushima and Chernobyl can result in pulses of radioactivity entering the forest environment. Due to intense recycling in the forest, equilibrium between radioactivity concentrations in trees and in soil may not be reached during the period of short-term radionuclide transport following the accident. Another question arises as to whether the equilibrium hypothesis using empirical concentration ratios (CRs) can be applied to the long-term period. Using two atmospheric 137Cs fallout scenarios in the Fukushima and Chernobyl sites, this study investigated whether the CR approach could provide conservative predictions of 137Cs levels in trees following 137Cs fallout events by comparing predictions from the CR approach using data gathered for trees by the IAEA to those from dynamic transfer models and actual measured data. The inter-comparisons also aimed to investigate whether the CR approach could account for the variability of 137Cs levels across different tree organs. The results showed that caution may be necessary when using the CR approach, which relies on the IAEA dataset, to estimate 137Cs accumulation in forest trees in the short - and long term following atmospheric 137Cs fallout events. A calculation by TRIPS 2.0 demonstrated the importance of considering the distribution within tree organs for in-depth analysis of radiological impact of forest trees. Our findings suggest that it may be preferable to use CR values based on site-specific data rather than generic data collected from various sites. This is particularly relevant when studying the sites where the bioavailability of 137Cs for trees and thus possible exposures are higher. This study also showed that dynamic modeling approaches could offer an alternative means of estimating CR values of the entire tree or specific tree organs in situations where empirically derived values are not available.

Urban Heat Island Dynamics in an Urban–Rural Domain with Variable Porosity: Numerical Methodology and Simulation

Heat transfer and fluid dynamics modeling in porous media is a widely explored topic in physics and applied mathematics, and it involves advanced numerical methods to address its non-linear nature. One interesting application has been the urban-heat-island (UHI) numerical simulation. The UHI is a negative consequence of the increasing urbanization in cities, which is defined as the presence of warm temperatures inside the urban canopy in contrast to the colder surroundings. Furthermore, an interesting phenomena occurs within a UHI context when the city transitions from a heat island to a cold island, matching the increases and decreases of solar radiation over the span of a day, as well as the decrease in the UHI intensity as a result of wind action. The numerical study in this paper had, as its main goal, to reproduce this phenomenon. Therefore, the key elements proposed in this work were the following: A 2D horizontal urban–rural domain that had a variable porosity with a Gaussian distribution centered in the city center. A non-stationary Darcy–Forchheimer–Brinkman model to simulate the flow in porous media, combined with an air–soil heat transport model linked by a balancing equation for the surface energy that includes the evapotranspiration of plants. In regards to the numerical resolution of the model, a classical numerical methodology based on the finite elements of Lagrange P1 type combined with explicit and implicit time-marching schemes have been effective for high-quality numerical simulations. Several numerical tests were performed on a domain inspired by the metropolitan region of Guadalajara (Mexico), in which not only the temperature inversion was reproduced but also the simulation of the UHI transition by strong wind gusts.

Study on dynamic model and dynamic characteristics of Delingha 50 MW trough solar field

China General Nuclear Power Group (CGNPC) Delingha 50 MW parabolic trough solar thermal power plant is the first commercial trough solar plant in China, and its solar field consists of 190 parallel heat collecting loops. For large-scale trough solar plant, balancing the flow rate of heat absorbing medium in each loop and stabilizing the outlet temperature are the key technologies and difficult problems. Regarding the Delingha 50 MW solar field as the research object, this paper mainly focusing on the dynamic characteristics of flow and heat transfer in the solar field. The hydrodynamic calculation model and the heat transfer dynamic model are established on the real-time dynamic simulation platform STAR-90. With the actual operation data, the built solar field model is validated by comparing the simulation results. On this basis, the disturbance simulations of direct normal irradiance (DNI), heat transfer oil’s mass flow and heat transfer oil’s inlet temperature are carried out. The dynamic response curves of disturbance and the thermal inertia time constant of the loops are obtained. The conclusions lay a theoretical foundation for the formulation of outlet medium’s temperature control strategy in the solar field of large-scale trough solar thermal power generation system.

Study on Dynamic Model and Dynamic Characteristics of Solar Field of 50 Mw Trough Solar Thermal Power Generation Plant

Solar thermal power generation solves the problem of fluctuation and intermittency through energy storage system, and can bear the basic power load and peak load regulation. It is an important technical way for China's energy structure transformation. As a complex thermal system with multivariable disturbance, large inertia and large delay, the operation control of the solar field is a difficult issue. In this paper, the solar field of the first 50 MW trough solar thermal demonstration power plant in China is taken as the research object. Based on the topological structure and working principle of the solar field and the basic laws of optics and thermodynamics, the hydrodynamic calculation model and the heat transfer dynamic model are developed. The correctness of the model is verified by comparing the simulation results with the actual operation data. On this basis, the disturbance simulations are carried out. In addition, the dynamic response curves of step disturbance and the inertia time constant of the heat collecting loops are obtained. The conclusions of this paper have important guiding significance for the operation control strategy formulation and system optimization design of trough solar thermal power generation system.

Electric heater mathematical model for cyber-physical systems

The article discusses the heat and mass transfer dynamic model for an electric heater with lumped parameters, which allows transient processes simulation for the main influences. The proposed model is recommended to be used in cyber-physical systems for forecasting and evaluating the effectiveness of control systems integrated into a single information management system. The developed model can be used by specialists for the analysis and synthesis of control systems for balanced ventilation systems or industrial air conditioners. As an example, a numerical simulation of transient processes along the action main channels for an electric heater HE 36/2 manufactured by VTS CLIMA was carried out. The significant advantage of the proposed model is the possibility for using it for the synthesis and analysis of multidimensional control systems.

In situ experimental exposure of fruit-bearing shoots of apple trees to 13CO2 and construction of a dynamic transfer model of carbon

Evaluating the transfer and metabolism of carbon (C) in apple fruit is key to estimating the potential accumulation of atmospheric 14C in fruit near and around nuclear facilities. We developed a dynamic compartment model for apple fruit-bearing shoots, assuming that the shoots are a simple unit of source and sink for photoassimilates. Fruit-bearing shoots of Malus domestica “Fuji” at different fruit growth stages were exposed to 13CO2in situ, followed by sampling at 72 h after exposure or at harvest. The 13C/(13C+12C) mole ratio in fruits, leaves, and current branch were measured to construct a five-compartment model of 13C (fruit, each fast and slow component of leaves, and current branch). The C inventories in the compartments were presented in accordance with the measured growth curves of C in the organs. The model simulated the 13C dynamics in plant tissues well. Simulation results of photoassimilate distribution using the model indicated that the retention of photoassimilated C at the harvest depended on the growth rate of C in the organs at the exposure.

Air Pollution Prediction Using an Ensemble of Dynamic Transfer Models for Multivariate Time Series

Entering a new era of big data, analysis of large amounts of real-time data is important, and air quality data as streaming time series are measured by several different sensors. To this end, numerous methods for time-series forecasting and deep-learning approaches based on neural networks have been used. However, they usually rely on a certain model with a stationary condition, and there are few studies of real-time prediction of dynamic massive multivariate data. Use of a variety of independent variables included in the data is important to improve forecasting performance. In this paper, we proposed a real-time prediction approach based on an ensemble method for multivariate time-series data. The suggested method can select multivariate time-series variables and incorporate real-time updatable autoregressive models in terms of performance. We verified the proposed model using simulated data and applied it to predict air quality measured by five sensors and failures based on real-time performance log data in server systems. We found that the proposed method for air pollution prediction showed effective and stable performance for both short- and long-term prediction tasks. In addition, traditional methods for abnormality detection have focused on present status of objects as either normal or abnormal based on provided data, we protectively predict expected statuses of objects with provided real-time data and implement effective system management in cloud environments through the proposed method.

Semifluidized Bed Adsorption Column Studies for Simultaneous Removal of Aqueous Phase Pb2+ and Cd2+ by Composite Adsorbents: an Experimental and Mass Transfer Dynamic Model–Based Approach

In this present work, the performance of a semifluidized bed adsorption column has been evaluated for the removal of Pb2+ and Cd2+ in a semi-continuous mode. The composite adsorbents have been synthesized from waste biomass–based biochar and alginate-based biopolymer. Synthesized adsorbent characterized and finally tested its effectiveness in the removal of both Pb2+ and Cd2+ metal ions by batch and semifluidized bed column adsorption studies. The adsorptive removal efficiencies were found to be dependent on solution pH, initial metal ion concentration, adsorbent dose or initial bed height, static bed height, system temperature and inlet flow rate of semifluidized bed operation. Pseudo-second-order kinetic model was fitted to the batch adsorption experimental data by non-linear and linear regression method and it was found that the non-linear method gives a better way of obtaining the various kinetic parameters and its applicability. A solute phase mass transfer–based dynamic model has been developed to explain the adsorptive behaviour of metal ions onto adsorbents during the semi-continuous mode of operation of a semifluidized bed system. Various mass transfer parameters and degree of dispersion coefficients for the individual packed and fluidized section were obtained from the developed model.

Aqueous phase phenol removal from synthetic and real steel plant effluents through a batch and Semifluidized bed column operation: Experimental and model analysis

In this present research, an attempt has been made for performance analysis of a semifluidized bed (SFBR) column operation with a low-cost biomass based-adsorbent for the removal of phenol from synthetic aqueous solution and actual steel plant effluents. The solid phase of gas-solid-liquid SFBR operation was Ca-alginate –biochar composite adsorbent beads which were prepared from low-cost agricultural solid waste-derived sugarcane bagasse biochar capture in Calcium-alginate. In batch adsorption study, the various physicochemical process parameters like temperature, initial phenol concentration, pH and adsorbent doses were identified and its effects on the phenol adsorptive removal and adsorption mechanism were studied. In a semi-fluidized bed column (SFBR) operation, the effect of adsorbents loading (bed height), initial phenol concentration, and liquid flow rate on phenol removal efficiency were studied. The 65 % bed efficiency performance of the semifluidized bed system was found with actual raw steel plant effluents and BOD, COD, TS etc. are also removed during actual steel plant effluents treatment operation. Finally, a mass transfer dynamic model has been developed and the model predicts the degree of axial dispersion of the system and the overall mass transfer coefficient of the system. Results suggested that this three-phase semifluidized bed composite bed adsorption column operation is suitable for industrial phenol bearing wastewater treatment.

Thermal and Fluid Dynamic Performance Comparison of Three Nanofluids in Microchannels Using Analytical and Computational Models

The fluid dynamic and thermal performance of three nanofluids containing aluminum oxide, copper oxide, and silicon dioxide nanoparticles dispersed in 60:40 ethylene glycol and water base fluid as a coolant in a microchannel heatsink are compared here by two methods. The first is a simple analytical analysis, which is acceptable for very low nanoparticle volumetric concentration (1–2%). The second method is a rigorous three-dimensional finite volume conjugate heat transfer and fluid dynamic model based upon a constant heat flux boundary condition, which is applicable for cooling electronic chips. The fluids’ thermophysical properties employed in the modeling are based on empirically derived, temperature dependent correlations from the literature. The analytical and computational results for pressure drop and Nusselt number were in good agreement with the nanofluids showing a maximum difference of 4.1% and 2.9%, respectively. Computations cover the practical range of Reynolds number from 20 to 200 in the laminar regime. Based on equal Reynolds number, all of the nanofluids examined generate a higher convective heat transfer coefficient in the microchannel than the base fluid, while copper oxide provided the most significant increase by 21%. Based on the analyses performed for this study, nanofluids can enhance the cooling performance of the heatsink by requiring a lower pumping power to maintain the same maximum wall temperature. Aluminum oxide and copper oxide nanofluids of 2% concentration reduce the pumping power by 23% and 22%, respectively, while maintaining the same maximum wall temperature as the base fluid.

Comparison of different dynamic thermal performance prediction models for the flat-plate solar collector with a new V-corrugated absorber

The flat-plate solar collector with a V-corrugated absorber (VFPC) has been shown to be able to improve the steady-state optical and thermal efficiency by up to 15.8% and 10.7%, respectively. To predict the dynamic thermal performance of VFPC, the Quasi-Dynamic Test Model (QDTM), Transfer Function Model (TFM) and Dynamic Heat Transfer Model (DHTM) are compared in this study. The coefficients of the dynamic test models (including QDTM and TFM) are obtained by the regression of experimental data, and the DHTM is presented based on the analysis of detailed heat transfer processes inside collector. Tested data under four kinds of test conditions is selected to identify parameters in the dynamic test models, and tested data under one more test condition with varied solar irradiances, fluid inlet temperatures and mass flow rates is selected to validate the prediction accuracy of the three models. For the short-term prediction results by QDTM/TFM/DHTM, the maximum absolute value of relative error of fluid outlet temperature Tfo and rate of useful heat gain Qu are 6.8%/5.5%/3.0% and 64.9%/43.8%/29.6% respectively. While for the long-term prediction results with the operation period of about 1 h, the averaged absolute value of relative error of useful heat gain Qu.o are 1.4%/1.0%/1.2% and the averaged absolute error of averaged thermal efficiency ηt.o are 1.1%/0.8%/0.9%. Results indicate that the DHTM has the most potential to predict the short-term thermal characteristic of VFPC accurately, followed by the TFM and QDTM, while the three kinds of models have the similar accuracy level to predict the long-term thermal characteristic of VFPC.

Dynamical charge transfer model for high surface charge density triboelectric nanogenerators

Triboelectric nanogenerators have made great progress and paved the way for green energy, self-powered implantable medical devices and a large number of sensors in the Internet of Things. Maxwell's displacement current is the fundamental theoretical framework of nanogenerators. Quantum model of charge transfer between atoms have been devoted to understanding the triboelectric effect. Increasing the output power of triboelectric nanogenerators is one of the most important subjects for practical application. Here, we study the charge transfer process in triboelectric materials and propose a triboelectric material charge transfer dynamic model. Dynamic charge transfer enables triboelectric nanogenerators to achieve high surface charge density and the superior device robustness, which can significantly improve the output power and life time of triboelectric nanogenerators. The charge transfer model provides not only deeply understanding for high performance of triboelectric nanogenerator, but also a useful guide for the optimization and design of high performance triboelectric materials.

Nitrate green removal by fixed-bed columns packed with waste biomass: Modelling and friction parameter estimation

Natural and waste waters pollution by nitrates is considered a major environmental problem due to the possible consequences on human health and on water bodies through eutrophication phenomenon. Hazelnut shell were employed as packing material in a large lab-scale column for the removal of nitrate from wastewaters, comparing the process performances with those obtained in batch system. A nitrate removal efficiency up to about 67% was observed in batch mode at low pH and with a sorbent mass concentration of 8 g/L with 0.5 mm size. A lower (62%) nitrate removal efficiency was observed at large lab-scale column, though notable volumes of effluents (60–200 L, depending on the inlet flow-rate) were successfully treated with a bed height of 30 cm and a sorbent mass of 590 g. Non-linear regression of batch equilibrium data using Langmuir, Freundlich and SIPS models allowed to estimate the isotherm parameters, subsequently used in a mass transfer dynamic model to fit the experimental data. The regressed film mass transfer coefficient kf, at six different inlet flowrate values were elaborated for the estimation of the characteristic parameters of the empirical correlation between Sherwood, Reynolds and Schmidt numbers. Furthermore, the pressure drop along the column was calculated and the Ergun and Carman equations were employed for the estimation of the empirical friction parameters.

Modeling and Simulation of a Novel Combined Solar Photovoltaic-Thermal Panel and Heat Pump Hybrid System

A numerical simulation model for a novel concept of a hybrid composed of photovoltaic-thermal solar panels and a heat pump is presented. This concept was developed to assess the performance and energy conversion efficiency of the hybrid system used to produce domestic hot water and electricity. A two-dimensional heat transfer and fluid flow dynamic model was developed to describe the behavior of the hybrid system under different solar irradiance, heat pump boundary conditions and different refrigerants. The model is based on dynamic mass and energy equations coupled with the heat transfer coefficients, and the thermodynamic properties of refrigerants as well as material properties. The model compared fairly to experimental data.

A dynamic model of training transfer

We expand our understanding of the training transfer process by developing the Dynamic Transfer Model (DTM). We develop and examine linkages between intentions to transfer, the initial attempts to utilize training, and the integration of feedback received from the transfer attempt. We propose that this process repeats itself over time in subsequent transfer attempts to impact work behavior and performance. Implications for transfer criteria, the dynamic interaction between the trainee and context, and the personalization of transfer are discussed. Based on the DTM, we suggest future research directions that can enrich our understanding of transfer as well as derive practical implications for improving training effectiveness.

The VATO project: Development and validation of a dynamic transfer model of tritium in grassland ecosystem

In this paper, a dynamic compartment model with a high temporal resolution has been investigated to describe tritium transfer in grassland ecosystems exposed to atmospheric 3H releases from nuclear facilities under normal operating or accidental conditions. TOCATTA-χ model belongs to the larger framework of the SYMBIOSE modelling and simulation platform that aims to assess the fate and transport of a wide range of radionuclides in various environmental systems. In this context, the conceptual and mathematical models of TOCATTA-χ have been designed to be relatively simple, minimizing the number of compartments and input parameters required. In the same time, the model achieves a good compromise between easy-to-use (as it is to be used in an operational mode), explicative power and predictive accuracy in various experimental conditions.In the framework of the VATO project, the model has been tested against two-year-long in situ measurements of 3H activity concentration monitored by IRSN in air, groundwater and grass, together with meteorological parameters, on a grass field plot located 2 km downwind of the AREVA NC La Hague nuclear reprocessing plant, as was done in the past for the evaluation of transfer of 14C in grass. By considering fast exchanges at the vegetation-air canopy interface, the model correctly reproduces the observed variability in TFWT activity concentration in grass, which evolves in accordance with spikes in atmospheric HTO activity concentration over the previous 24 h. The average OBT activity concentration in grass is also correctly reproduced. However, the model has to be improved in order to reproduce punctual high concentration of OBT activity, as observed in December 2013. The introduction of another compartment with a fast kinetic (like TFWT) - although outside the model scope - improves the predictions by increasing the correlation coefficient from 0.29 up to 0.56 when it includes this particular point. Further experimental investigation will be undertaken by IRSN and EDF next year to better evaluate (and properly model) other aspects of tritium transfer where knowledge gaps have been identified in both experimental and modelling areas.

Impact of the Fukushima accident on marine biota, five years later.

In a previous commentary written in 2011 in the aftermath of the Fukushima accident in Japan, I summarized what was then understood about the effects of accidental radioactive discharges to marine life and forecasted into the future how the marine environment would likely be affected. Since that time, several studies have been conducted on the impact of the accident on marine organisms, and radiation doses arising thereof. I developed a dynamic transfer model for studying the bioaccumulation of Fukushima radionuclides in marine biota and assessed the impact and likelihood of effects to marine life. In the present article, I highlight the lessons learned over the past 5 years. I address whether the environmental consequences in the marine environment are as significant as initially feared and, with respect to the current situation, what remains to be investigated as the radioactivity continues to spread in the marine environment. Integr Environ Assess Manag 2016;12:654-658. © 2016 SETAC.

Aeration optimization through operation at low dissolved oxygen concentrations: Evaluation of oxygen mass transfer dynamics in different activated sludge systems

In wastewater treatment plants (WWTPs) using the activated sludge process, two methods are widely used to improve aeration efficiency — use of high-efficiency aeration devices and optimizing the aeration control strategy. Aeration efficiency is closely linked to sludge characteristics (such as concentrations of mixed liquor suspended solids (MLSS) and microbial communities) and operating conditions (such as air flow rate and operational dissolved oxygen (DO) concentrations). Moreover, operational DO is closely linked to effluent quality. This study, which is in reference to WWTP discharge class A Chinese standard effluent criteria, determined the growth kinetics parameters of nitrifiers at different DO levels in small-scale tests. Results showed that the activated sludge system could meet effluent criteria when DO was as low as 0.3mg/L, and that nitrifier communities cultivated under low DO conditions had higher oxygen affinity than those cultivated under high DO conditions, as indicated by the oxygen half-saturation constant and nitrification ability. Based on nitrifier growth kinetics and on the oxygen mass transfer dynamic model (determined using different air flow rate (Q′air) and mixed liquor volatile suspended solids (MLVSS) values), theoretical analysis indicated limited potential for energy saving by improving aeration diffuser performance when the activated sludge system had low oxygen consumption; however, operating at low DO and low MLVSS could significantly reduce energy consumption. Finally, a control strategy coupling sludge retention time and MLVSS to minimize the DO level was discussed, which is critical to appropriate setting of the oxygen point and to the operation of low DO treatment technology.

A Dynamic Heat Transfer Model to Predict the Thermal Response of a Tank Exposed to a Pool Fire

Large scale storage of bulk flammable fuels is necessary for distribution of fuel and also provides an opportunity to take advantage of and minimize market risk due to price fluctuations. Due to the inherent flammable properties of fuels, process safety is a key factor in the design of large scale fuel storages, in terms of instrumentation, detail design, emergency preparedness and site layout. In this paper we will describe a method to calculate important input data for the site layout, fire cooling water requirements and the time one can expect will elapse until a fire spreads from one tank to another. To achieve this, a model to calculate emitted radiation from a fire, and the dynamic response and effect on exposed targets is derived.Much data and models, in terms of emitted radiation, is available on traditional fossil fuels, less is available for ethanol and other renewable biofuels. In this paper reviewed experimental data of both fossil fuels and recent data of biofuels is used to fit a radiation model that takes into account type of fuel and size of pool fire to calculate emitted radiation. When it comes to determine the tar gets received radiation, several view factor models are available in the literature. In this paper a modified view factor model is derived to enable calculation of the effect of both wind speed and site topography. Finally a first principle heat transfer model is derived to calculate the thermal response on affected nearby storage tanks in the vicinity of a pool fire. This model takes the following heat transfer mechanisms into account: received radiation, cooling by convection, cooling by radiation on the inside of the tank and cooling by radiation on the outside of the tank.Finally, the model is compared to reviewed experimental data and similar models to evaluate the accuracy in terms of response times for fire spread and radiation levels.