scholarly journals Fluid Dynamic Approaches for Prediction of Spray Drift from Ground Pesticide Applications: A Review

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1182
Author(s):  
Se-woon Hong ◽  
Jinseon Park ◽  
Hanna Jeong ◽  
Seyeon Lee ◽  
Lakyeong Choi ◽  
...  

Spray drifts have been studied by mathematical models and computer simulations as an essential complement to lab and field tests, among which are fluid dynamic approaches that help to understand the transport of spray droplets in a turbulent atmosphere and their potential impacts to the environment. From earlier fluid mechanical models to highly computational models, scientific advancement has led to a more realistic prediction of spray drift, but the current literature lacks reviews showing the trends and limitations of the existing approaches. This paper is to review the literature on fluid-mechanical-based modelling of spray drift resulting from ground spray applications. Consequently, it provides comprehensive understanding of the transition and development of fluid dynamic approaches and the future directions in this research field.

2019 ◽  
Vol 26 (8) ◽  
pp. 1311-1327 ◽  
Author(s):  
Pala Rajasekharreddy ◽  
Chao Huang ◽  
Siddhardha Busi ◽  
Jobina Rajkumari ◽  
Ming-Hong Tai ◽  
...  

With the emergence of nanotechnology, new methods have been developed for engineering various nanoparticles for biomedical applications. Nanotheranostics is a burgeoning research field with tremendous prospects for the improvement of diagnosis and treatment of various cancers. However, the development of biocompatible and efficient drug/gene delivery theranostic systems still remains a challenge. Green synthetic approach of nanoparticles with low capital and operating expenses, reduced environmental pollution and better biocompatibility and stability is a latest and novel field, which is advantageous over chemical or physical nanoparticle synthesis methods. In this article, we summarize the recent research progresses related to green synthesized nanoparticles for cancer theranostic applications, and we also conclude with a look at the current challenges and insight into the future directions based on recent developments in these areas.


2021 ◽  
Vol 13 (6) ◽  
pp. 3089
Author(s):  
Miquel Torrent ◽  
Pedro Javier Gamez-Montero ◽  
Esteban Codina

This article presents a methodology for predicting the fluid dynamic behavior of a gear pump over its operating range. Complete pump parameterization was carried out through standard tests, and these parameters were used to create a bond graph model to simulate the behavior of the unit. This model was experimentally validated under working conditions in field tests. To carry this out, the pump was used to drive the auxiliary movements of a drilling machine, and the experimental data were compared with a simulation of the volumetric behavior under the same conditions. This paper aims to describe a method for characterizing any hydrostatic pump as a “black box” model predicting its behavior in any operating condition. The novelty of this method is based on the correspondence between the variation of the parameters and the internal changes of the unit when working in real conditions, that is, outside a test bench.


2021 ◽  
Vol 54 (2) ◽  
pp. 1-36
Author(s):  
Sameen Maruf ◽  
Fahimeh Saleh ◽  
Gholamreza Haffari

Machine translation (MT) is an important task in natural language processing (NLP), as it automates the translation process and reduces the reliance on human translators. With the resurgence of neural networks, the translation quality surpasses that of the translations obtained using statistical techniques for most language-pairs. Up until a few years ago, almost all of the neural translation models translated sentences independently , without incorporating the wider document-context and inter-dependencies among the sentences. The aim of this survey article is to highlight the major works that have been undertaken in the space of document-level machine translation after the neural revolution, so researchers can recognize the current state and future directions of this field. We provide an organization of the literature based on novelties in modelling and architectures as well as training and decoding strategies. In addition, we cover evaluation strategies that have been introduced to account for the improvements in document MT, including automatic metrics and discourse-targeted test sets. We conclude by presenting possible avenues for future exploration in this research field.


2021 ◽  
pp. 47-54
Author(s):  
И.А. Болодьян ◽  
С.В. Пузач ◽  
А.С. Барановский

Рассматривается вопрос выбора расчетной сетки при моделировании пожара в тоннеле с помощью полевого метода и проводится оценка возможного влияния размеров ячеек сетки, а также граничного условия постоянства давления на результаты расчета. Выполнено моделирование пожара для четырех размеров расчетной сетки. Обоснована возможность применения наиболее грубой из используемых сеток с точки зрения инженерных расчетов, в том числе с оговоркой относительно постановки граничного условия. The issue of fire safety of road tunnels is currently an urgent task. Road tunnels are usually not standard typical facilities, but the unique structures. Therefore, it is necessary to study the influence of various parameters on the development of fire in order to take into account the characteristics of a particular object and make decisions on its effective fire protection. Implementation of field tests in this case is expensive and time-consuming. In this regard, numerical modeling is one of the most effective methods of such research. Field models are the most common and currently used for numerical calculations. These models are based on the numerical solution of the system of conservation equations for small control volumes of the calculation grid. This paper examines the issues of selection the calculation grid when modeling a fire in tunnels using the field method is considered and the possible influence of the size of the grid cells is estimated. The mathematical model used in this work is based on a set of differential equations of hydrodynamics, heat transfer, as well as the equation of conservation of the masses of components. Four computational grids were selected for a horizontal (without slope) model tunnel to determine the optimal cell size. As a result of conducted calculations it was established the following: the size of calculated grid is not fundamental for the initial stage of the fire; the use of smaller grid may be preferable at further development of fire, accompanied by increase of combustion capacity to the maximum; the maximum temperature values, especially in the far sections, are obtained on the coarsest grid. The use of such a grid for estimated engineering calculations can be allowed.


Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3015 ◽  
Author(s):  
Jijian Lian ◽  
Hongzhen Wang ◽  
Haijun Wang

Research on the safety of powerhouse in a hydropower station is mostly concentrated on the vibration of machinery structure and concrete structure within a single unit. However, few studies have been focused on the vibration transmission among units. Due to the integrity of the powerhouse and the interaction, it is necessary to study the vibration transmission mechanism of powerhouse structure among units. In this paper, field structural vibration tests are conducted in an underground powerhouse of a hydropower station on Yalong River. Additionally, the simplified mechanical models are established to explain the transmission mechanism theoretically. Moreover, a complementary finite element (FE) model is built to replicate the testing conditions for comprehensive analysis. The field tests results show that: (1) the transmission of lateral-river vibration is greater than those of longitude-river vibration and vertical vibration; (2) the vibration transmission of the vibrations that is caused by the low frequency tail fluctuation is basically equal to that of the vibrations caused by rotation of hydraulic generator. The transmission mechanism is demonstrated by the simplified mechanical models and is verified by the FE results. This study can provide guidance for further research on the vibration of underground powerhouse structure.


2021 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Eva Wiese ◽  
Agnieszka Wykowska

The present chapter provides an overview from the perspective of social cognitive neuroscience (SCN) regarding theory of mind (ToM) and joint attention (JA) as crucial mechanisms of social cognition and discusses how these mechanisms have been investigated in social interaction with artificial agents. In the final sections, the chapter reviews computational models of ToM and JA in social robots (SRs) and intelligent virtual agents (IVAs) and discusses the current challenges and future directions.


2009 ◽  
Vol 6 (4) ◽  
pp. 6441-6489 ◽  
Author(s):  
S. Duggen ◽  
N. Olgun ◽  
P. Croot ◽  
L. Hoffmann ◽  
H. Dietze ◽  
...  

Abstract. Iron is a key micronutrient for phytoplankton growth in the surface ocean. Yet the significance of volcanism for the marine biogeochemical iron-cycle is poorly constrained. Recent studies, however, suggest that offshore deposition of airborne ash from volcanic eruptions is a way to inject significant amounts of bio-available iron into the surface ocean. Volcanic ash may be transported up to several tens of kilometres high into the atmosphere during large-scale eruptions and fine ash may encircle the globe for years, thereby reaching even the remotest and most iron-starved oceanic areas. Scientific ocean drilling demonstrates that volcanic ash layers and dispersed ash particles are frequently found in marine sediments and that therefore volcanic ash deposition and iron-injection into the oceans took place throughout much of the Earth's history. The data from geochemical and biological experiments, natural evidence and satellite techniques now available suggest that volcanic ash is a so far underestimated source for iron in the surface ocean, possibly of similar importance as aeolian dust. Here we summarise the development of and the knowledge in this fairly young research field. The paper covers a wide range of chemical and biological issues and we make recommendations for future directions in these areas. The review paper may thus be helpful to improve our understanding of the role of volcanic ash for the marine biogeochemical iron-cycle, marine primary productivity and the ocean-atmosphere exchange of CO2 and other gases relevant for climate throughout the Earth's history.


2021 ◽  
Author(s):  
Fabrizio Zausa ◽  
Luigi Besenzoni ◽  
Alessandro Caia ◽  
Seda Mizrak

Abstract The disaster of Macondo of 2010 changed the rules in reliability and safety standards during drilling operations. New regulations were developed in order to improve the control level on blowout risk, and all upstream operators adopted innovative technologies capable to reduce the potential risk of uncontrolled release, either by decreasing its frequency of occurrence or the expected impacts. The objective of this paper is to present a Quantitative Risk Analysis (QRA) of well blowout and measure the beneficial contribution of intervention technologies in terms of expected reduction of spill volume and associated costs. The QRA is applied to any kind of well operation (drilling, completion, workover, light intervention) and well type. The methodology relies upon different risk analysis techniques able to quantify the residual blowout risk, as well as the mitigation provided by each technology. Through Fault Tree Analysis (FTA), a value of blowout probability is calculated for each well operation. The initial blowout condition is associated with a blowout flow rate, calculated with fluid dynamic computational models depending on well flow path and release point into the environment. The evolution of each release scenario is then studied with the use of Event Tree Analysis (ETA), where a set of events, able to reduce or stop the flow, are considered with their probability of success and occurrence time (well bridging, water coning, surface intervention through killing/capping techniques, relief well operations). The value of each intervention is estimated through Decision Tree Analysis (DTA), calculating the amount of spill volume reduction and avoided spill costs. Results of spill volume and cost reduction are calculated for a set of specific wells, considering the application of killing/capping systems as well as Eni innovative technologies. The benefit of these interventions is measured in terms of Expected Monetary Value (EMV) in relation to a potential release extinguished by a relief well, which is the decisive intervention to stop the blowout, considered as the worst case scenario. Surface interventions with killing/capping techniques are the major contributors to the reduction of blowout impacts, and all additional measures which can be adopted should act in the fastest way possible before the arrival of heavy capping stack system. The main innovative contribution of the proposed QRA methodology is the association of an expected economic value to post-blowout mitigation techniques, which takes into account all possible uncertainties related to their success and intervention time. Moreover, by evaluating an economic impact of the residual spill cost, it is possible to prioritize and increase the overall efficiency of the oil spill response plan for each operational and geographical context, and improve the control on blowout risk mitigation process.


Author(s):  
Haoxiang Xia ◽  
Huili Wang ◽  
Zhaoguo Xuan

As a key sub-field of social dynamics and sociophysics, opinion dynamics utilizes mathematical and physical models and the agent-based computational modeling tools, to investigate the spreading of opinions in a collection of human beings. This research field stems from various disciplines in social sciences, especially the social influence models developed in social psychology and sociology. A multidisciplinary review is given in this paper, attempting to keep track of the historical development of the field and to shed light on its future directions. In the review, the authors discuss the disciplinary origins of opinion dynamics, showing that the combination of the social processes, which are conventionally studied in social sciences, and the analytical and computational tools, which are developed in mathematics, physics and complex system studies, gives birth to the interdisciplinary field of opinion dynamics. The current state of the art of opinion dynamics is then overviewed, with the research progresses on the typical models like the voter model, the Sznajd model, the culture dissemination model, and the bounded confidence model being highlighted. Correspondingly, the future directions of this academic field are envisioned, with an advocation for closer synthesis of the related disciplines.


Author(s):  
Erandi Lakshika ◽  
Michael Barlow

Computational aesthetics is an area of research that attempts to develop computational methods that can perform human-like aesthetic judgements. Aesthetic judgements are often subjective, and as such, the development of computational models of aesthetics is highly challenging. This chapter summarizes the advancements in the area of computational aesthetics and how computational intelligence techniques are applied in art and aesthetics ranging from simple classification problems to more advanced problems such as automatic generation of art artefacts, stories, and simulations. The chapter concludes by summarizing major challenges that need to be addressed, and future directions that need to be undertaken in order to make significant advancements in the area of computational aesthetics and its applications.


Sign in / Sign up

Export Citation Format

Share Document