Energy Preservation Research Articles

Experimental and computational study of melting phase-change material for energy storage in shell and tube heat exchanger

The preservation of thermal energy is a significant problem that needs to be resolved. In the present energy demand situation, effective storage of available energy will be a technique to manage the gap between the demand and supply. Solar energy is one such energy, which is an easily obtainable and renewable source of energy. Still, the maximum employment of solar energy is not readily possible without the implementation of the thermal energy storage system (TESS). This TESS can be an integral part of solar applications, thus TESS acts as a reservoir of energy to deliver the energy requirement at all times. Hence, it is an appropriate system to unite the energy source, i.e., the sun and the applications. Thus, the TESS is very vital in solar applications. The main objective of this work is to design and analyze the vertical shell and tube type TESS using water as heat transfer fluid (HTF) and paraffin wax RT58 as phase change material (PCM), which is subjected to change its phase at 46 °C to 68 °C from solid to liquid when exposed to higher temperatures, and its operating temperature range is 60 °C to 80 °C. Here, PCM (RT58) is enclosed in the tubes of the shell and tube storage unit. The property of the high specific heat capacity of PCM is tested for utilization of latent heat storage that can be used any time as required. Temperature measurements are taken using a T-type thermocouple along with an indicator and a series of experiments were conducted to study the effects of PCM in TESS. PCM encapsulated heat exchanger performance is investigated for both charging and discharging cycles with 85 °C inlet water temperature and a constant flow rate of 0.04 kg/s. To analyze the melting characteristics of PCM, simulation is carried out using ANSYS Fluent in the workbench, and comparative simulation studies are carried out for quadrilateral and triangular node shapes for better accuracy with experimental data. The heat energy stored in the charging cycle is 302.327 kJ for 100 min duration, and in discharging cycle is 295.8 kJ for 56 min duration. The HTC and Nusselt number were also calculated for both the charging and discharging cycle. It is evident from the present work, that the PCM can act as a better alternate for energy storage medium compared with the present solar energy storage methods, ensuring the correct adaptability of PCM for the particular application. The heat transfer rate can be increased further by using more amounts of different PCM or PCM composite with higher latent heat and also by providing better tank insulation. In future work, emulsification of nanomaterial in the PCM or in the HTF, and implementation of finned tube profile can increase the overall performance of TESS.

Beyond appetite regulation: Targeting energy expenditure, fat oxidation, and lean mass preservation for sustainable weight loss.

New appetite‐regulating antiobesity treatments such as semaglutide and agents under investigation such as tirzepatide show promise in achieving weight loss of 15% or more. Energy expenditure, fat oxidation, and lean mass preservation are important determinants of weight loss and weight‐loss maintenance beyond appetite regulation. This review discusses prior failures in clinical development of weight‐loss drugs targeting energy expenditure and explores novel strategies for targeting energy expenditure: mitochondrial proton leak, uncoupling, dynamics, and biogenesis; futile calcium and substrate cycling; leptin for weight maintenance; increased sympathetic nervous system activity; and browning of white fat. Relevant targets for preserving lean mass are also reviewed: growth hormone, activin type II receptor inhibition, and urocortin 2 and 3. We endorse moderate modulation of energy expenditure and preservation of lean mass in combination with efficient appetite reduction as a means of obtaining a significant, safe, and long‐lasting weight loss. Furthermore, we suggest that the regulatory guidelines should be revisited to focus more on the quality of weight loss and its maintenance rather than the absolute weight loss. Commitment to this research focus both from a scientific and from a regulatory point of view could signal the beginning of the next era in obesity therapies.

Autophagy and the Energy Status of Plant Cells

In plant cells the homeostatic control of energy balance involves the production and recycling of adenylates with macroergic bonds, ATP and ADP. The maintenance of anabolic processes requires the relative saturation of the adenylate pool with high energy phosphoanhydride bonds. The bulk of ATP synthesis is carried out both in mitochondria and in chloroplasts while optimal ATP levels within other cell compartments are maintained by adenylate kinases (AK). AK activity was recently found in cytosol, mitochondria, plastids and the nucleus. ATP synthesis in energy-producing organelles, as well as redistribution of nutrients among cellular compartments, requires fine-tuned regulation of ion homeostasis. A special role in energy metabolism is played by autophagy, a process of active degradation of unwanted and/or damaged cell components and macromolecules within the central lytic vacuole. So-called constitutive autophagy controls the quality of cellular contents under favorable conditions, i.e., when the cellular energy status is high. Energy depletion can lead to the activation of the pro-survival process of autophagic removal and utilization of damaged structures; the breakdown products are then used for ATP regeneration and de novo synthesis of macromolecules. Mitophagy and chlorophagy maintain the populations of healthy and functional energy-producing “stations”, preventing accumulation of defective mitochondria and chloroplasts as potential sources of dangerous reactive oxygen species. However, the increase of autophagic flux above a threshold level can lead to the execution of the vacuolar type of programmed cell death (PCD). In this case autophagy also contributes to preservation of energy through support of the outflow of nutrients from dying cells to healthy neighboring tissues. In plants, two central protein kinases, SnRK1 (Snf1-related protein kinase 1) and TOR (target of rapamycin), are responsible for the regulation of the metabolic switch between anabolic and catabolic pathways. TOR promotes the energy-demanding metabolic reactions in response to nutrient availability and simultaneously suppresses catabolism including autophagy. SnRK1, the antagonist of TOR, senses a decline in cellular energy supply and reacts by inducing autophagy through several independent pathways. Here, we provide an overview of the recent knowledge about the interplay between SnRK1 and TOR, autophagy and PCD in course of the regulation of energy balance in plants.

Construction of metal organic framework-derived hollow-structured mesoporous carbon based lithium hydroxide composites for low-grade thermal energy storage

Benefiting from its remarkable storage capacity and long energy preservation life-span, salt hydrate thermochemical energy storage (TCES) materials build a passable bridge between renewable energy and residential heating. To the best of our knowledge, the application of carbon matrix derived from metal organic frameworks (MOFs) in TCES have not been reported so far. Herein, a brand new LiOH TCES composite with salt hydrate uniformly dispersed in an activated hollow carbon (AHC) with a hollow mesoporous structure derived from the hollow zeolite imidazolate framework is prepared and fully characterized. The resulting Li/AHC2 composite is equipped with excellent hydration performance while exhibiting a maximum heat storage capacity of 1757.1 kJ kg−1 with low working temperature owing to the synergistic effect of cavity structure, large surface area and diversified porosity of AHC2. Besides, compared with pure LiOH, the Li/AHC2-50 with significantly enhanced thermal conductivity can still maintain 90.2% of the original heat storage capacity after 15 dehydration-hydration cycles, highlighting its outstanding fatigue resistance and huge heat transfer application potential. This study not only becomes a new dawn for the effective use of available low-temperature heat sources, but may also inspire new thoughts for expanding the implementation territory of carbon materials derived from MOFs.

Effect of Nelumbo nucifera Petals Extract on Antioxidant Activity and Sperm Quality in Charolais Cattle Sperm Induced by Mancozeb.

The white Nelumbo nucifera petals aqueous extraction (NAE) was prominent in phytochemical content, antioxidant activity, and enhanced rat sperm viability induced by FeSO4, a heavy metal. Mancozeb (MZ) contains heavy metals and is widely used for fungal control in agriculture and industry. It induces oxidative stress and causes of spermatogenesis and reproductive organs’ abnormalities in both humans and animals. The aims of the present study were to investigate the effects of white Nelumbo nucifera petals aqueous extraction (WNAE) on sperm quality in cattle sperm induced by MZ. Moreover, this study investigated phytochemical compounds by liquid chromatography-mass spectrometry. A protein profile related to sperm quality with SDS-page and sperm energy preservation for each treatment was determined. The results found nine phytochemical compounds, in which quercetin-3-O-arabinoglycoside was a major flavonoid that was found in the WNAE. MZ induced free radicals in cells, leading to LPO and protein oxidation, while decreasing sperm motility, sperm viability, acrosome integrity, and normal sperm morphology. The cattle sperm found four proteins related to sperm quality including MWs of 17, 31, 34, and 55 kDa. The WNAE effectively increased energy preservation, sperm motility, sperm viability, acrosome integrity, and normal sperm morphology. The WNAE enhanced sperm qualities by reducing oxidative stress. It might be suggested that WNAE has benefits for sperm preservation which may be used to guard against toxicity in animals or humans exposed to MZ contaminants.

Will sailing in formation reduce energy consumption? Numerical prediction of resistance for ships in different formation configurations

In nature, emergent collective behaviors suggest that the followers would obtain energy benefit from positive interaction with the leader’s wake by certain configurations. This article answers the question about the motivation of formation control research -- “will sailing in formation reduce energy consumption”. We carried out a series of numerical analyses on the relationship between resistance and formation configurations using the Reynolds Averaged Navier-Stokes (RANS) method in combination with the Shear Stress Transport (SST) k-ω turbulence model. At the first stage, verification and four-separate-distance benchmark cases are conducted to test grid discretization and numerical methods. Then, parametric studies are performed at various longitudinal offsets and transverse separations in tandem, parallel, and triangle formations. The numerical results indicate that specific formation configurations could bring resistance reduction and achieve energy benefit from the perspective of the whole convoy and the individual ship. Discussions on the resistance, energy consumption, and formation configuration are provided, respectively. Five energy consumption regions are established based on the resistance variations under different formation configurations. In terms of energy preservation, tandem formation is the optimal fleet configuration, followed by the triangle and parallel formation. Besides, for better maneuverability, specific longitudinal distances and lateral gaps are given to eliminate the additional lateral force and yaw moment caused by the ship-ship interaction.

Machine-learning energy-preserving nonlocal closures for turbulent fluid flows and inertial tracers

Machine learning turbulence closures for non-homogeneous and non-isotropic flows is a challenging task. The novelty of the presented approach is the adoption of a universal constraint associated with the energy preservation of the nonlinear terms, which is valid for any turbulent system. This constraint is embedded in the training process, and in combination with nonlocal representations in space and time, results in significant improvement for the resulted coarse scale models.

Optimal Convergence and Long-Time conservation of Exponential Integration for Schrödinger Equations in a Normal or Highly Oscillatory Regime

In this paper, we formulate and analyse exponential integrations when applied to nonlinear Schrödinger equations in a normal or highly oscillatory regime. A kind of exponential integrators with energy preservation, optimal convergence and long time near conservations of density, momentum and actions is formulated and analysed. To this end, we propose continuous-stage exponential integrators and show that the integrators can exactly preserve the energy of Hamiltonian systems. Three practical energy-preserving integrators are presented. We establish that these integrators exhibit optimal convergence and have near conservations of density, momentum and actions over long times. A numerical experiment is carried out to support all the theoretical results presented in this paper. Some applications of the integrators to other kinds of ordinary/partial differential equations are also discussed.

Von Neumann Stability Analysis of DG-Like and PNPM-Like Schemes for PDEs with Globally Curl-Preserving Evolution of Vector Fields

This paper examines a class of involution-constrained PDEs where some part of the PDE system evolves a vector field whose curl remains zero or grows in proportion to specified source terms. Such PDEs are referred to as curl-free or curl-preserving, respectively. They arise very frequently in equations for hyperelasticity and compressible multiphase flow, in certain formulations of general relativity and in the numerical solution of Schrödinger’s equation. Experience has shown that if nothing special is done to account for the curl-preserving vector field, it can blow up in a finite amount of simulation time. In this paper, we catalogue a class of DG-like schemes for such PDEs. To retain the globally curl-free or curl-preserving constraints, the components of the vector field, as well as their higher moments, must be collocated at the edges of the mesh. They are updated using potentials collocated at the vertices of the mesh. The resulting schemes: (i) do not blow up even after very long integration times, (ii) do not need any special cleaning treatment, (iii) can operate with large explicit timesteps, (iv) do not require the solution of an elliptic system and (v) can be extended to higher orders using DG-like methods. The methods rely on a special curl-preserving reconstruction and they also rely on multidimensional upwinding. The Galerkin projection, highly crucial to the design of a DG method, is now conducted at the edges of the mesh and yields a weak form update that uses potentials obtained at the vertices of the mesh with the help of a multidimensional Riemann solver. A von Neumann stability analysis of the curl-preserving methods is conducted and the limiting CFL numbers of this entire family of methods are catalogued in this work. The stability analysis confirms that with the increasing order of accuracy, our novel curl-free methods have superlative phase accuracy while substantially reducing dissipation. We also show that PNPM-like methods, which only evolve the lower moments while reconstructing the higher moments, retain much of the excellent wave propagation characteristics of the DG-like methods while offering a much larger CFL number and lower computational complexity. The quadratic energy preservation of these methods is also shown to be excellent, especially at higher orders. The methods are also shown to be curl-preserving over long integration times.

Soft-cooperation via data sharing eases transboundary conflicts in the Lancang-Mekong River Basin

Water resources management in the Lancang-Mekong River Basin (LMRB) is challenging in face of the complex trans-national geopolitical context, the acceleration of hydropower dam expansion, and the growing demands for energy, food, and riverine ecosystem preservation across the basin. Centralised management through coordinated operation of all the basin water infrastructures (“hard cooperation”) across the river basin is ideal but hard to achieve given the existing geopolitical context of the region. To overcome these barriers and facilitate a more adaptive and reliable operation of the LMRB’s water system, this paper focuses on the concept of “soft-cooperation”, i.e. the idea of indirectly fostering cooperation by sharing data across countries to inform the non-cooperative (or independent) operation of their systems. Here, we first quantify existing riparian conflicts and synergies for the non-cooperative scenario, where upstream and downstream act independently without any form of cooperation, and for the “hard cooperation” configuration, where an ideal centralised operator jointly operates all the infrastructures. Then a “soft cooperation” scheme assuming data sharing across riparian countries is evaluated. The most effective and informative data is selected via machine learning and used to inform the design of the river reservoir system operation via evolutionary multiobjective direct policy search. Results show that the riparian conflicts around water mainly exist between the sectors, i.e. hydropower production vs ecosystem conservation, rather than among countries. For reservoirs with various capacities and locations, the value of information varies. Generally, sharing data about the water currently available in the different river storages results in a large improvement in hydropower production. This study highlights the value of appropriate data sharing and selection in water system operation as an indirect way of promoting cooperation in transboundary river management.

Reinterpretation and extension of entropy correction terms for residual distribution and discontinuous Galerkin schemes: Application to structure preserving discretization

For the general class of residual distribution (RD) schemes, including many finite element (such as continuous/discontinuous Galerkin) and flux reconstruction methods, an approach to construct entropy conservative/ dissipative semidiscretizations by adding suitable correction terms has been proposed by Abgrall ((2018) [1]). In this work, the correction terms are characterized as solutions of certain optimization problems and are adapted to the SBP-SAT framework, focusing on discontinuous Galerkin methods. Novel generalizations to entropy inequalities, multiple constraints, and kinetic energy preservation for the Euler equations are developed and tested in numerical experiments. For all of these optimization problems, explicit solutions are provided. Additionally, the correction approach is applied for the first time to obtain a fully discrete entropy conservative/dissipative RD scheme. Here, the application of the deferred correction (DeC) method for the time integration is essential. This paper can be seen as describing a systematic method to construct structure preserving discretization, at least for the considered example.

Arbitrary high-order linearly implicit energy-preserving algorithms for Hamiltonian PDEs

In this paper, we present a novel strategy to systematically construct linearly implicit energy-preserving schemes with arbitrary order of accuracy for Hamiltonian PDEs. Such a novel strategy is based on the newly developed exponential scalar auxiliary variable (ESAV) approach that can remove the bounded-from-below restriction of nonlinear terms in the Hamiltonian functional and provides a totally explicit discretization of the auxiliary variable without computing extra inner products. So it is more effective and applicable than the traditional scalar auxiliary variable (SAV) approach. To achieve arbitrary high-order accuracy and energy preservation, we utilize symplectic Runge-Kutta methods for both solution variables and the auxiliary variable, where the values of the internal stages in nonlinear terms are explicitly derived via an extrapolation from numerical solutions already obtained in the preceding calculation. A prediction-correction strategy is proposed to further improve the accuracy. Fourier pseudo-spectral method is then employed to obtain fully discrete schemes. Compared with the SAV schemes, the solution variables and the auxiliary variable in these ESAV schemes are now decoupled. Moreover, when the linear terms have constant coefficients, the solution variables can be explicitly solved by using the fast Fourier transform. Numerical experiments are carried out for three Hamiltonian PDEs to demonstrate the efficiency and conservation of the ESAV schemes.

Energy Efficient Order Picking Routing for a Pick Support Automated Guided Vehicle (Ps-AGV)

Order picker routing refers to the process of collecting a set of products with the minimum travel time. Recently, a new generation of Automated Guided Vehicles (AGVs) has been developed to assist human order pickers in order to minimize their travel time. These vehicles are using battery as energy source. However, the routing energy efficiency aspect of these systems remains unexplored. Yet any improvement in power consumption will ultimately reduce the DOD (depth of discharge) of the battery and increase its lifespan. For example, in many real AGV applications incorporating the effect of load mass has been neglected, although its importance. In most studies, the methodology proposed for the order picking routing problem does not allow neither the integration of the mass of each Stock Keeping Unit (SKU) nor the calculation of associated energy costs. Those studies are generally limited to ensure that all the items requested by an order are picked up with minimum travel time/distance. In this paper, an Energy Efficient Order Picking Routing algorithm named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EE-OPR</i> is proposed to realize an efficient AGV tour with an acceptable trade-off between energy preservation and travel time minimization. The proposed approach takes into account the mass of loads and its accumulation throughout the pick tour since it intensifies the rolling resistance losses on flat ground, especially at lower speeds. In this regard, an optimization method by means of dynamic states graph is developed. This method is applied to different warehouse layouts. The performance of the suggested algorithm is evaluated by comparing it with an approach minimizing only travel time consumption. Results show that the optimized tours, offered by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EE-OPR</i> are effective and robust, with an 18% average saving on the total cost of picking tour.

High-order symplectic Lie group methods on &lt;inline-formula&gt;&lt;tex-math id="M1"&gt;$ SO(n) $&lt;/tex-math&gt;&lt;/inline-formula&gt; using the polar decomposition

&lt;p style='text-indent:20px;'&gt;A variational integrator of arbitrarily high-order on the special orthogonal group &lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ SO(n) $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; is constructed using the polar decomposition and the constrained Galerkin method. It has the advantage of avoiding the second order derivative of the exponential map that arises in traditional Lie group variational methods. In addition, a reduced Lie–Poisson integrator is constructed and the resulting algorithms can naturally be implemented by fixed-point iteration. The proposed methods are validated by numerical simulations on &lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ SO(3) $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; which demonstrate that they are comparable to variational Runge–Kutta–Munthe-Kaas methods in terms of computational efficiency. However, the methods we have proposed preserve the Lie group structure much more accurately and and exhibit better near energy preservation.&lt;/p&gt;

Seismic attenuation compensation with spectral-shaping regularization

Because of the viscoelasticity of the subsurface medium, seismic waves will inherently attenuate during propagation, which lowers the resolution of the acquired seismic records. Inverse-Q filtering, as a typical approach to compensating for seismic attenuation, can efficiently recover high-resolution seismic data from attenuation. Whereas most efforts are focused on compensating for high-frequency energy and improving the stability of amplitude compensation by inverse-Q filtering, low-frequency leakage may occur as the high-frequency component is boosted. In this article, we propose a compensation scheme that promotes the preservation of low-frequency energy in the seismic data. We constructed an adaptive shaping operator based on spectral-shaping regularization by tailoring the frequency spectra of the seismic data. We then performed inverse-Q filtering in an inversion scheme. This data-driven shaping operator can regularize and balance the spectral-energy distribution for the compensated records and can maintain the low-frequency ratio by constraining the overcompensation for high-frequency energy. Synthetic tests and applications on prestack common-reflection-point gathers indicated that the proposed method can preserve the relative energy of low-frequency components while fulfilling stable high-frequency compensation.

Reinforcement Energy Efficient ant Colony Optimization of Mobile Ad Hoc Multipath Routing Performance Enhancement

The Mobile Ad hoc Network (MANET) is a collection of mobile nodes that operates without infrastructure and is self-administrative. It often changes the topology called dynamic network. The nodes are in the dynamic network spending more energy on path finding that resultant the node quickly draining and being inactive in the network. To overcome this issue, propose an Improve Energy Capability Backup Route ant colony optimization (IEC-BR) algorithm for reducing energy usage, enhancing network lifetime, improving packet delivery, and decreasing end-to-end delay. The algorithm uses a backup route for minimizing the route researching and node energy preservation. Stability factors and Quality of Services (QoS) parameters help to enhance the network lifetime and QoS. The stability factor uses the node residual energy and the link lifetime. Hop count and bandwidth are used for the QoS parameters. The simulation result has proved the proposed IEC-BR technique improves packet delivery, node lifetime by 31% and reduces the network delay compared to the traditional Ad hoc On-demand Distance Vector (AODV) and Multi Objective Ad hoc On-demand Distance Vector (MOAODV) routing protocols.

Autoregressive moving average based anycast with support vector machine clustering in mobile ad‐hoc networks

AbstractNodes in mobile ad‐hoc networks (MANETs) are battery‐powered, therefore, need energy‐efficient techniques to cut down the cost of energy consumption. Energy consumption is directly related to route discovery, which could be reduced through anycasting. Anycast is an operation in MANETs, where the source sends messages to one particular destination node of anycast region. In general, the message transmitted is divided into certain packets, and those are transmitted continuously one after the other through selected routes. If the link from anycast source to destination breaks in between or an anycast destination goes out of the anycast region, in that case, a new anycast destination will have to be selected on a new route to the destination. This will incur huge message costs and energy. In this work, we select desirable anycast destinations based on their eligibility by using autoregressive moving average and support vector machine. Eligibility is modeled as a function of residual energy, location, the relative velocity concerning neighbors, and the number of packets successfully forwarded earlier by those neighbors' locations. Reducing the number of anycast receivers reduces the message cost of protocols significantly. We have compared our protocol's performance with the same of anycast‐AODV, anycast‐DSR, anycast‐FAIR, and MQAR (mobility and QoS‐aware anycast routing protocol) results show significant improvement. Collective improvement amounts to 89% more energy preservation and 39% delay on average.

Future Trends and Aging Analysis of Battery Energy Storage Systems for Electric Vehicles

The increase of electric vehicles (EVs), environmental concerns, energy preservation, battery selection, and characteristics have demonstrated the headway of EV development. It is known that the battery units require special considerations because of their nature of temperature sensitivity, aging effects, degradation, cost, and sustainability. Hence, EV advancement is currently concerned where batteries are the energy accumulating infers for EVs. This paper discusses recent trends and developments in battery deployment for EVs. Systematic reviews on explicit energy, state-of-charge, thermal efficiency, energy productivity, life cycle, battery size, market revenue, security, and commerciality are provided. The review includes battery-based energy storage advances and their development, characterizations, qualities of power transformation, and evaluation measures with advantages and burdens for EV applications. This study offers a guide for better battery selection based on exceptional performance proposed for traction applications (e.g., BEVs and HEVs), considering EV’s advancement subjected to sustainability issues, such as resource depletion and the release in the environment of ozone and carbon-damaging substances. This study also provides a case study on an aging assessment for the different types of batteries investigated. The case study targeted lithium-ion battery cells and how aging analysis can be influenced by factors such as ambient temperature, cell temperature, and charging and discharging currents. These parameters showed considerable impacts on life cycle numbers, as a capacity fading of 18.42%, between 25–65 °C was observed. Finally, future trends and demand of the lithium-ion batteries market could increase by 11% and 65%, between 2020–2025, for light-duty and heavy-duty EVs.

Data-driven simulation of multivariate nonstationary wind velocity with explicit introduction of the time-varying coherence functions

An S-transform (ST) based data-driven simulation methodology is proposed of multivariate nonstationary wind velocity with explicit introduction of the time-varying coherence functions. This framework differs from that based on the evolutionary spectral theory that uniform or non-uniform modulation functions needs to be assigned. In defining the time-frequency power spectral density (TFPSD) in accordance with the ST coefficients, the Parseval's theorem is considered to ensure energy preservation. The proposed method is firstly applied to simulated nonstationary wind velocity. For comparisons, the results of the discrete orthonormal S transform (DOST) are also included. The research demonstrates that the ST based results agree well with the original, but a bias exists between the results simulated by DOST and the original, indicating that the feasibility of the proposed method. Employing four measured downburst records to simulate multivariate nonstationary wind velocity by the proposed method further validates its feasibility. In order to enhance the simulation fidelity, the inverse S-transform (IST) based regulation and control method (IST-RCM) of high precision is developed, where the balancing parameter is defined and formulated to express quantitatively the relationship between accuracy and efficiency. It is found that the results with IST-RCM get more close to the actual wind velocity records.

Sowing date as a response to ecological conditions in maize seed production

The environment protection, energy, and resources preservation are especially pronounced under present climate changes. In agriculture, these changes are recognised as drought, high temperatures, occurrence of stormy winds and hail. The aim of this study was to determine variations in seed morphology that are a result of different sowing dates in relation with agro- ecological conditions of maize (Zea mays L.) cultivation. The material used for the study encompassed three inbred lines (G1, G2, G3) sown every 10 d on five sowing dates (T1, T2, T3, T4, T5) starting from 1 April to 10 May, during 2 yr (Y1: 2018, Y2: 2019). The following physical properties of seeds were estimated: width (W), length (L), thickness (Tk), ratio of small (SF) to large fraction (LF) and grain yield (GY). The width was the highest in all three inbreeds on T4 (1.00, 1.03, 0.99 cm, respectively); T5 was the least favourable date for L (1.09, 1.12, 1.09 cm, respectively) while Tk was the lowest in G1 (0.51 cm) and G2 (0.51 cm) sown on T1. The most significant differences in the formation of physical properties occurred in seeds sown on T5 (p ≤ 0.05). The highest differences were observed in width between T5-T4 (-0.223 cm), in length between T5-T2 (-0.309 cm) and in thickness between T5-T3 (-0.129 cm). Later sowing dates favoured LF (85.2%) in comparison to SF (14.7%). Seed size variability participated with 50% in yield formation (R2 ≥ 0.5).