Energy Balance Principle Research Articles

Neo-Hookean modeling of nonlinear coupled behavior in circular plates supported by micro-pillars

In the contemporary era, the enhancement of wearable capacitive sensors is achieved through the utilization of polymeric micropillars as filler materials between electrode plates. To gain a deeper understanding of the dynamic response of the system, nonlinear coupled governing equations of a circular microplate motion resting on an array of polymeric micropillars have been derived. These equations are used to model the system’s behavior. In addition, the squeezing motion of the micro-pillars is characterized using the incompressible Neo-Hookean model. Both static and dynamic responses, including transient and steady-state solutions, are investigated in detail by discretizing over spatial coordinates using a weak formulation approach. A frequency response analysis is conducted using a continuation-based method. This entails expanding the steady-state solution using a Fourier transform and employing the energy balance principle. The unknown coefficients of the expansion series are calculated using a gradient descent-based learning approach that is physically motivated. Furthermore, a dynamic step size strategy for frequency increments is employed to effectively follow the solution path. This strategy is implemented via the ARC length method. In this study, we examine the impact of varying PDMS (polydimethylsiloxane) hydrogel mechanical and geometrical configurations. It can be reasonably concluded that the mechanical properties of the pillars and the geometrical configuration of the circular plate and micropillars have a significant impact on the maximum tolerable pressure, fast transient response, and frequency response analysis.

Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation.

The environmental control of layer houses with multi-tiered cage systems is influenced by factors such as the structure of the henhouses and the heat dissipation of the flock, leading to low precision and large fluctuations in temperature control. Based on a new combined positive- and negative-pressure ventilation (CPNPV) mode, a dynamic temperature model is constructed. Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). First, based on the principles of energy and mass balance, and by decoupling the relationship between positive- and negative-pressure ventilation volumes, a dynamic temperature model for layer houses under CPNPV was established. Then, the PID parameters and the proportional relationship between positive- and negative-pressure ventilation were optimized through fuzzy rules, and a proportional exponential function was introduced to adjust the scaling of the universe, enabling fine-tuned control. Finally, a temperature control model for the layer house was built using Simulink. The results show that the coefficients of determination (R2) of the constructed dynamic temperature models are between 0.79 and 0.88, respectively, indicating high accuracy. The designed VFPID method outperformed traditional on-off control and improved control precision by 20-23.53% and 10.34-22.22% compared with PID control and fuzzy PID(FPID) control methods, respectively. This study provides new insights for the development of environmental control equipment and precise environmental regulation of layer houses.

Assessment of Spatiotemporal Variations in Actual Evapotranspiration using the pySEBAL Model and Remote Sensing Data in Navsari, Gujarat, India

Evapotranspiration (ET), encompassing both transpiration from plants and evaporation from the Earth's surface, is a vital component of the hydrological cycle and influences water and energy exchanges between the surface and the atmosphere. This study investigates the application of the Surface Energy Balance Algorithm for Land (SEBAL) to estimate actual evapotranspiration (AET) over a selected region. The study area, located in Navsari district of Gujarat, India, was characterized by varying climates and land cover conditions. Cloud-free LANDSAT 8 satellite images were utilized at a spatial resolution of 30 x 30 meters to execute the SEBAL model within the Python-built GRASSGIS software. The SEBAL algorithm, based on the principles of energy balance, calculates AET by considering net radiation, sensible heat flux, and ground heat flux. The results showed that AET correlated with factors such as vegetation cover, land surface temperature, and net radiation. The AET rates exhibited significant spatial and temporal variations, with the highest rates observed in May and the lowest in months with reduced net radiation. Across the study area, the dominant AET rate ranges from 3 to 6 mm/day during the summer months and from 2 to 3 mm/day during the winter months. This pattern encompasses more than 65% of the total study area. Moreover, the highest AET values derived from the SEBAL model are contrasted with potential ET (PET) estimates obtained through diverse empirical techniques. This analysis demonstrates a robust alignment between SEBAL-based AET and PET calculations. Notably, in the months of April and May, when the peak AET closely corresponds to PET, there is a potential indication of impending water scarcity concerns.

Mass Conservative Time-Series GAN for Synthetic Extreme Flood-Event Generation: Impact on Probabilistic Forecasting Models

The lack of data on flood events poses challenges in flood management. In this paper, we propose a novel approach to enhance flood-forecasting models by utilizing the capabilities of Generative Adversarial Networks (GANs) to generate synthetic flood events. We modified a time-series GAN by incorporating constraints related to mass conservation, energy balance, and hydraulic principles into the GAN model through appropriate regularization terms in the loss function and by using mass conservative LSTM in the generator and discriminator models. In this way, we can improve the realism and physical consistency of the generated extreme flood-event data. These constraints ensure that the synthetic flood-event data generated by the GAN adhere to fundamental hydrological principles and characteristics, enhancing the accuracy and reliability of flood-forecasting and risk-assessment applications. PCA and t-SNE are applied to provide valuable insights into the structure and distribution of the synthetic flood data, highlighting patterns, clusters, and relationships within the data. We aimed to use the generated synthetic data to supplement the original data and train probabilistic neural runoff model for forecasting multi-step ahead flood events. t-statistic was performed to compare the means of synthetic data generated by TimeGAN with the original data, and the results showed that the means of the two datasets were statistically significant at 95% level. The integration of time-series GAN-generated synthetic flood events with real data improved the robustness and accuracy of the autoencoder model, enabling more reliable predictions of extreme flood events. In the pilot study, the model trained on the augmented dataset with synthetic data from time-series GAN shows higher NSE and KGE scores of NSE = 0.838 and KGE = 0.908, compared to the NSE = 0.829 and KGE = 0.90 of the sixth hour ahead, indicating improved accuracy of 9.8% NSE in multistep-ahead predictions of extreme flood events compared to the model trained on the original data alone. The integration of synthetic training datasets in the probabilistic forecasting improves the model’s ability to achieve a reduced Prediction Interval Normalized Average Width (PINAW) for interval forecasting, yet this enhancement comes with a trade-off in the Prediction Interval Coverage Probability (PICP).

Development and Testing of Small-Scale Flash Dryer for Maize Bran

Sun drying is the most common technique used to dry various food products due to its economic convenience. However, it is not effective owing to its unreliable nature leading to microbial deterioration and aflatoxin contamination of food. In Tanzania, about 1.3 million tonnes of maize bran are at risk of deterioration annually due to improper drying. The aim of this study was to design, fabricate and test an efficient small-scale flash dryer for maize bran. Using principles of material and energy balance, a small-scale flash dryer with a throughput of 500 kg of dry product per hour was designed resulting in a nominal diameter of 387 mm and a drying length of 20 m. Design calculations and drawings were done using MS Excel 2021 and SolidWorks 2018 respectively. Empirical procedures were used to fabricate and test the dryer. The material of construction used in the flash duct was food grade (stainless steel, SS 201). A fuel blend of Waste Engine Oil (WEO) and diesel (85%-15%) was used with a novel heavy oil burner. It was observed that at an inlet air temperature of 150 °C and air velocity of 12 m/s, moist maize bran was dried from 37% to 10% w.b. The fabricated flash dryer's energy efficiency, specific energy consumption, and specific energy utilization are 74%, 3.4 MJ/kg water evaporated, and 1.71 MJ/kg dry maize bran respectively. It was concluded that the fabricated small-scale flash dryer displayed improved energy performance compared to others presented in literature. Better instrumentation was recommended for feedback control on burner operation and process monitoring which further enhances the performance of the fabricated small-scale flash dryer.

НОРМИРОВАНИЕ ВОДОПОТРЕБЛЕНИЯ СЕЛЬСКОХОЗЯЙСТВЕННЫХ УГОДИЙ И КУЛЬТУР С УЧЕТОМ ПРОСТРАНСТВЕННО-ВРЕМЕННОЙ ИЗМЕНЧИВОСТИ ГИДРОМЕТЕОРОЛОГИЧЕСКИХ ФАКТОРОВ

The article presents the developed calculation methodology for environmental regulation of water consumption of agricultural land and crops, taking into account the spatiotemporal variability of climatic, hydrological, soil and biological indicators of the natural system. It is noted that the human pressure in the form of a deficit in water consumption of agricultural land and crops should be based on the principles of energy balance of heat, moisture and nutrients, taking into account natural conditions that ensure targeted regulation and management of soil-forming processes in hydro-agrolandscapes. The developed model and algorithm for assessing water consumption in agriculture are built using two models for rationing water consumption - agricultural land and crops, which makes it possible to determine the most important criteria for environmental management in irrigated agriculture and is of great importance in ensuring food security of the population.

Predicting distribution of aeolian vibration amplitude of undamped overhead transmission lines

The most widely accepted estimation procedure of the severity of aeolian vibration is by calculating the maximum oscillation amplitudes of the conductor using Energy Balance Principle (EBP). However, the EBP is based on wind tunnel results where only one frequency is excited, while observations and experimental results show that multiple resonant modes are excited simultaneously. Furthermore, the required number of cycles of each amplitude level is not provided by current EBP-based methods. In this paper, vibration data from an experimental undamped ACSR Bersfort test line in Quebec, Canada, is recorded and analyzed. For each record of aeolian vibrations, amplitudes are fitted to a Rayleigh distribution based on the narrow-band assumption. The number of cycles and Rayleigh parameter are then related to wind conditions through a modified Strouhal frequency and EBP methodology. A statistical model is proposed to relate vibration profiles and wind input while considering wind turbulence intensity. The proposed method performs well and gives accurate estimates of both vibration amplitudes and number of cycles for ACSR Bersfort conductor. Physical and statistical theory is provided for each step of the method in order to extend the application of the method to other types of conductors or different line configurations.

Effect of the experimental parameters on the ice-asphalt adhesion strength and corresponding theoretical model based on the energy-balanced principle

Ice adhesion behavior plays a crucial role in assessing ice-phobic materials. However, the variation of ice-adhesion strength across different laboratories is attributed to the neglect of ice/substrate characteristics. In this work, ice-adhesion strength under different geometric parameters of ice/substrate on asphalt surfaces was examined through an optimized methodology. Additionally, a theoretical model was developed based on the energy balance principle to analyze the influence of various parameters on ice-adhesion strength and to make predictions. The results suggested that the ice-adhesion strength was positively correlated with the substrate thickness and negatively correlated with both the asphalt thickness and the ice diameter. The detachment process of the ice-asphalt interface was divided into two regions, the non-linear mechanical response region, and the linear damage region. The slope of the linear damage region can be defined as the interfacial stiffness of the ice-asphalt system, which was the main reason leading to the change in ice adhesion strength. The increase in ice-adhesion strength was observed as the interfacial stiffness increased. Moreover, the theoretical model of ice-adhesion strength illustrated the effect of ice/substrate geometric characteristics on ice-adhesion strength and was verified by the experiments. This study may provide some new references and a theoretical basis for further research on ice adhesion behavior in different laboratories.

Optimal economical sizing of a PV-battery grid-connected system for fast charging station of electric vehicles using modified snake optimization algorithm

This paper presents a methodology for the optimal sizing of a proposed photovoltaic (PV)-battery grid-connected system for fast charging station of electric vehicles (FCSEVs) in Cairo, Egypt. The key objectives of the formulated optimization problem are to minimize the total system cost and to guarantee the validity of the energy balance principle within the considered system. The paper also develops a novel energy management strategy, which is designed based on two widely adopted pricing strategies, for optimally managing the power flow within the considered system with the purpose of reaching the optimum sizes of the considered system components. In addition, the paper suggests a modification to the Snake optimization (SO) algorithm, which is used to solve the formulated optimization problem using MATLAB software. Moreover, a comparison is conducted among the proposed modified Snake optimization (MSO) algorithm and four other common meta-heuristic optimization algorithms to validate the viability of the suggested MSO algorithm in achieving the desired eventual aims of the sizing process. Furthermore, a techno-economic study is carried out to assess the economic viability of the proposed system for each of the two adopted pricing strategies over the project lifetime. The yielded results indicated that the developed energy management strategy is capable of managing the energy flow within the considered system effectively. Also, they demonstrated that the suggested MSO algorithm can yield the best optimal solutions for the formulated optimization problem for each of the two adopted pricing strategies compared to the other considered optimization algorithms.

Design and simulation of 30 000 tons per year of cumene plant from natural gas field

Abstract The research considers the design and simulation of 30 000 tons per year of cumene plant using Aspen HYSYS as the simulation tool. The feed (material content) used is the characterized natural gas from Utorogu Gas Field with composition of 0.9019 methane, 0.0694 ethane, 0.0209 propane, 0.00361 n-butane, 0.00414 i-butane, 0.00005 n-pentane and 0.00007 i-pentane. The cumene plant consist of the cryogenic distillation column, de-hydrogenator (Continuous Stirred Tank Reactor), Alkylator (Plug Flow Reactor), storage tanks, separators, pumps, heat exchanger and mixers. The size/design models of basic plant units such as de-hydrogenator, alkylator, separators, storage tanks and distillation column were developed using the principles of mass and energy balance. The result of design or size specifications in terms of equipment diameter of basic plant units obtained from HYSYS simulation are 0.8 m and 0.319 m for the cryogenic and cumene columns; 1.931 m, 2.244 m and 1.366 m for the propane, propene and cumene storage tanks; 1.868 m and 2.076 m for the de-hydrogenator and alkylator; 1.931 m and 2.146 m for propene and cumene separators respectively. The power or capacity of propane and propene pumps configured in the plant are 0.02 kW and 0.005 kW respectively. The result of the reactor and distillation column thickness specification to withstand corrosion, pressure or stress during plant operation in terms of cylindrical shell and ellipsoidal doomed head are 17.36 mm and 4.31 mm respectively. The economic evaluation (overall cost) including the cost of utilities, catalyst, operating, and maintenance for entire plant is $ 3.004 M.

Feasibility assessment of implementing energy pile-based snowmelt system on a practical bridge deck in diverse climate conditions across China

The accumulation of snow on roads poses substantial challenges to traffic flow, incurring profound human safety concerns and considerable financial losses. To address this issue, a cost-effective and environmentally friendly solution is presented in the form of an energy pile-based snowmelt system. This research provides a comprehensive framework, which integrates the principle of bridge deck energy balance and numerical models of energy pile and practical bridge deck, aiming to evaluate the feasibility of the system in diverse climatic zones across China. First, the long-term climate and geography data pertaining to the snowmelt heat flux demand for the investigated climate regions are gathered and correlated. The Pearson Correlation Coefficients (PCCs) of each parameter (99 % confidence interval) elucidate the strongest correlation between ambient temperature and heat flux demand. Employing the proposed framework, the subsequent feasibility assessment demonstrates that the system's snow-melting effect varies with regional climate and snowmelt targets, and when real-time snow-melting is nonessential (snow-free area ratio, Ar, with values of 0 and 0.5), the system is feasible in most cities except Mohe, where the ambient temperature (Ta) reaches −28.74 °C and the snowfall rate water equivalent (s) is 1.56 mm/h. However, the system fails to meet the real-time snow-melting goal (Ar = 1) when it is located in extreme climate (Ta < −17 °C or s > 1 mm/h). The findings also reveal that snowmelt systems exhibit consistent behavior within the same climate zone. The study provides valuable insights into the practical application of energy pile-based snowmelt systems in different climate conditions, and highlights the critical role of climate considerations in the successful implementation of such innovative technologies.

Numerical simulation of fracture temperature field distribution during oil and gas reservoir hydraulic fracturing based on unsteady wellbore temperature field model

In the hydraulic fracturing oil and gas reservoir, the temperature variation of the fracturing fluid has a great impact on its flow and rheology, affecting the sand-carrying capacity and friction resistance of the fracturing fluid, and also affecting the settling speed of proppant in the fracture, thus changing the sand setting profile and sand laying concentration, and finally affecting the geometry of the fracture. Based on the energy balance and continuity equations, a numerical model for the distribution of wellbore temperature field in an extended-reach well is developed, and a variation law for the wellbore and reservoir temperature fields during fracturing also is formulated. A 3D mathematical model of the temperature distribution in hydraulic fracture and near-fracture formations has been developed based on heat transfer theory and finite-difference methods, taking into account the temperature gradients of fracture length and height according to the energy balance principle and fracture fluid continuity equations. The sensitivity factors of the temperature field are clarified, the wellbore temperature field and the fracture matrix temperature field model are coupled, and the influence rule of the temperature field change of the construction layer on the fracture shape while fracturing is revealed, which provides a theoretical basis for the hydraulic fracturing design optimization.

A one-dimensional transient temperature prediction model for Chinese assembled solar greenhouses

The prediction of the thermal environment of greenhouses has always been an essential component of greenhouse development. In this paper, a one-dimensional transient temperature prediction model is constructed based on the principle of energy balance for Chinese assembled solar greenhouses (CASG). The daily temperature trends for each surface in the greenhouse were obtained by solving the model using MATLAB. The performance of the model was assessed by comparing the measured and predicted values. The mean absolute errors for the temperature of air, back roof, front roof, heat collector plate, north wall, ground and water storage tank were computed to be 1.4 °C, 1.89 °C, 1.98 °C, 2.07 °C, 2.26 °C, 1.44 °C and 0.68 °C, respectively. The results demonstrate a high level of concurrence between the simulated and measured values, indicating that the model is proficient in predicting the thermal environment of CASG. Based on this, predictions were made regarding the internal environment of CASG on both sunny and cloudy days, which contributes to a comprehensive understanding of the thermal environment. The research provides theoretical support for regulating environmental conditions of CASG.

Energy-based performance prediction for metals in powder bed fusion

The mechanical performance of metallic parts fabricated by powder bed fusion (PBF) additive manufacturing is directly linked to process variables. However, it remains challenging to rapidly forecast the resulting mechanical performance based on specified process conditions. To tackle this issue, this paper proposes a process-performance prediction model capable of efficiently estimating the yield strength (YS) and ultimate tensile strength (UTS) via used process parameters. The formation quality of metals related to energy absorptivity/consumption is first determined based on the energy balance principle during PBF. Subsequently, the effective properties of as-built metals with process-induced defects are obtained using a homogenization method. Considering the relation between the thermal energy and elastoplastic strain energy, the YS and the UTS of printed parts are effectively predicted based on the force-heat equivalence energy density principle. The accuracy of the proposed model is validated by the comparison with the literature. Furthermore, the effect of the main process variables on the YS and the UTS of printed metallic parts is demonstrated and analyzed. The results show an increase of YS and UTS followed by a gradual decrease with the key process variables increasing, including the volumetric energy density, length of scan vector, layer thickness, and environment temperature. These results can serve as a guideline for improving the mechanical performance of PBF-printed metals.

Stability Improvement for One Cycle Controlled Boost Converters Based on Energy Balance Principle

Stability Improvement for One Cycle Controlled Boost Converters Based on Energy Balance Principle

Toward Data Center Digital Twins via Knowledge-based Model Calibration and Reduction

Computational fluid dynamics (CFD) models have been widely used for prototyping data centers. Evolving them into high-fidelity and real-time digital twins is desirable for the online operations of data centers. However, CFD models often have unsatisfactory accuracy and high computation overhead. Manually calibrating the CFD model parameters is tedious and labor-intensive. Existing automatic calibration approaches apply heuristics to search the model configurations. However, each search step requires a long-lasting process of repeatedly solving the CFD model, rendering them impractical, especially for complex CFD models. This article presents Kalibre , a knowledge-based neural surrogate approach that calibrates a CFD model by iterating four steps of (i) training a neural surrogate model, (ii) finding the optimal parameters through neural surrogate retraining, (iii) configuring the found parameters back to the CFD model, and (iv) validating the CFD model using sensor-measured data. Thus, the parameter search is offloaded to the lightweight neural surrogate. To speed up Kalibre’s convergence, we incorporate prior knowledge in training data initialization and surrogate architecture design. With about ten hours of computation on a 64-core processor, Kalibre achieves mean absolute errors (MAEs) of 0.57°C and 0.88°C in calibrating the CFD models of two production data halls hosting thousands of servers. To accelerate CFD-based simulation, we further propose Kalibreduce that incorporates the energy balance principle to reduce the order of the calibrated CFD model. Evaluation shows the model reduction only introduces 0.1°C to 0.27°C extra errors while accelerating the CFD-based simulations by thousand times.

Simulation Of The Optimum Operating Conditions For A Propylene Glycol Production Unit Using Aspen Hysys Software

Commercially, propylene glycol is produced by the direct hydrolysis of propylene oxide with water. This first-order, irreversible, exothermic reaction is performed in a glass-lined Continuous Stirred Tank Reactor (CSTR). In this study, the initiation of a CSTR was modelled from first principles and simulated using Aspen Hysys 3.2 to obtain concentration and temperature profiles. It is often very important how these profiles approximate the steady-state values. For example, when approaching a steady state the temperature may rise too high and this leads to degradation of the reactant or product, or the altitude may be unacceptable for safe operation. If either condition occurs, the system will exceed its practical stability limit. The practical stability limit represents the temperature above which it is undesirable to operate due to undesirable side reactions or equipment damage. Therefore, the best-operating conditions were obtained in terms of the flow rate of the raw material and the temperature of the reactor at 345 Kgmol/h and 82.2 °C on straight. The production of propylene glycol in the presence of an acid catalyst in an isothermal tank reactor is presented using advanced process simulation software. The effect of temperature was also calculated using the principle of energy balance on the reactor. The reactor operates optimally at a fractional conversion of 0.995 to obtain optimal values for the most important variables/parameters [reactor volume 7.92 m3, reactor length 2.83 m, reactor diameter 1.89 m, and amount of heat required for cooling per unit volume of the reactor 1205 kw].

An energy-efficient and cleaner production of hydrogen by steam reforming of glycerol using Aspen Plus

Hydrogen (H2) is produced in an efficient and sustainable manner using steam reforming of glycerol in this work. Two models are used to provide anticipation about how efficiently H2 can be produced: Model 1, a stoichiometric model, and Model 2, a thermodynamic model. Model 1 helps determine the water/glycerol molar input ratio and reaction pathway. The thermodynamic feasibility of Model 1 is examined using Model 2, which then determines the optimum conditions for maximal H2 generation. Model 2 produced 1275 kmol/h of H2 with an H2 mole fraction of 0.49 at 658 °C and 1 atm of pressure. The reactor's net heat load is greatly reduced through heat integration in this study. The energy required is reduced by 29.5% as compared to when no heat integration is used. The process of separating and eliminating CO2 is accomplished by employing the principles of mass and energy balance in the Aspen Plus.

Ballistic prediction of ceramic armor backed by thin metal plate against threats of small and medium‐calibers

AbstractBased on the principle of energy balance, a new analytical model is established to estimate the ballistic performance of ceramic‐faced armor against small and medium‐caliber projectiles. The energy consumption of ceramic is described as the product of compressive strength and erosion volume of ceramic. Despite its simple form, it represents the main response characteristic of ceramic erosion. Moreover, considering the dependence of the fracture cone half‐angle on the ceramic/metal thickness ratio and projectile velocity, one has innovatively incorporated them in the present model to predict reasonably the half‐angle evolution. To further simplify the analytical calculation and facilitate its application, an explicit prediction formula of the central deflection on thin metal plate is adopted. Then, the accuracy of analytical prediction has been carefully checked with the ballistic test data of small and medium‐caliber projectiles to penetrate light ceramic‐faced armor. The satisfactory consistency between the experimental and analytical results has confirmed the validity of the present model. It is therefore expected to be a powerful tool for the optimal design of new ceramic‐faced armor.

DAMPING OF FINITE AMPLITUDE SOLITARY WAVES IN A FLUME

Solitary wave is a permanent wave when the dissipation is ignored. Many analytical solutions have been developed for finite amplitude solitary waves. In additional to the perturbation solutions, closed form solutions are also available (e.g., McCowan 1891, Clamond and Fructus 2003, being denoted as CF from hereon), which are more accuracy, especially for larger amplitude solitary waves which were discussed in Wang and Liu (2022). In Wang and Liu (2022) ’s laboratory experiments, solitary waves are slowly damped along the wave flume, which can be attributed to the energy dissipation inside the boundary layers on the bottom and sidewalls. Keulegan (1948) first derived an approximate solution to describe the wave damping in the wave flume for small amplitude solitary wave. The basic idea of calculating the damping effect is that the rate of energy dissipation inside the boundary layers must be the same as the rate of wave energy loss. In this work, the same principle of energy balance is adopted for calculating the wave damping for finite amplitude solitary waves in a wave flume. The closed form solutions provided in CF are employed here for analyses.