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We describe a new mathematical approach for deriving and solving covolume models of the three‐dimensional, incompressible Navier—Stokes flow equations. The approach integrates three technical components into a single modelling algorothm: automatic grid generation; covolume equation generation; dual variable reduction.

We describe a novel mathematical approach to deriving and solving covolume models of the incompressible 2‐D Navier‐Stokes flow equations. The approach integrates three technical components into a single modelling algorithm: 1. Automatic Grid Generation. An algorithm is described and used to automatically discretize the flow domain into a Delaunay triangulation and a dual Voronoi polygonal tessellation. 2. Covolume Finite Difference Equation Generation. Three covolume discretizations of the Navier‐Stokes equations are presented. The first scheme conserves mass over triangular control volumes, the second scheme over polygonal control volumes and the third scheme conserves mass over both. Simple consistent finite difference equations are derived in terms of the primitive variables of velocity and pressure. 3. Dual Variable Reduction. A network theoretic technique is used to transform each of the finite difference systems into equivalent systems which are considerably smaller than the original primitive finite difference system.

This paper reports on an investigation of the integration of symbolic computation and reasoning into highly computerized numerically‐based realtime control systems for complex plant process management. This is the natural next step in an evolving maturation of the use of computers for automated monitoring and control of continuous processes. A particular implementation involving nuclear power plant intelligent monitoring is being developed from which overall principles and specifications can be distilled, ultimately leading to a general methodology that can be applied to other continuous plant processes.

The purpose of this paper is to investigate how to determine optimal investing stopping time in a stochastic environment, such as with stochastic returns, stochastic interest rate and stochastic expected growth rate.

Transformation method was used for solving optimal stopping problem by providing a way to transform path‐dependent problem into a path‐independent one. Based on option pricing theory, optimal investing stopping time was thought of as an optimal executed timing problem of American‐style option.

First, the authors transform a path‐dependent stop timing problem to a path‐independent one with transformation under very general conditions, to directly use the existing conclusion of optimal stopping time literature. Second, when dynamics of capital growth is homogeneous, the authors changed the two dimensional optimal stop timing problem into a single dimension problem based on the assumption of zero exercise costs. Third, the authors investigated the comparative dynamics about asset selling boundary on asset value, state variable and return predictability. With constant discount rate and growth rate, the optimal selling timing depends on the simple comparison between capital cost and growth rate.

The paper's contributions to analysis method may be as follows. The authors demonstrate how to transform a path‐dependent stopping problem into a path‐independent one under general conditions. The transform method in this article can be applied to other path‐dependent optimal stopping problems. In particular, a Riccati ordinary differential equation for the transformation is set up. In most examples commonly met in finance, the equation can be solved explicitly.

The Reduced Basis Method (RBM) generates low-order models of parametrized PDEs to allow for efficient evaluation of parametrized models in many-query and real-time contexts. The purpose of this paper is to investigate the performance of the RBM in microwave semiconductor devices, governed by Maxwell's equations.

The paper shows the theoretical framework in which the RBM is applied to Maxwell's equations and present numerical results for model reduction under geometry variation.

The RBM reduces model order by a factor of $1,000 and more with guaranteed error bounds.

Exponential convergence speed can be observed by numerical experiments, which makes the RBM a suitable method for parametric model reduction (PMOR).

Hail risk management is essential for successful farm management in German fruit production, particularly because hail events and associated losses have increased in recent years. The purpose of this paper is to conduct a detailed risk analysis comparing different strategies to manage hail risk, taking into account farmers’ risk aversion and farm-specific conditions.

Within an expected utility framework, two different strategies for managing hail risk are compared: one belonging to the group of financial instruments (hail insurance) and the other to the group of technical instruments (anti-hail net). A unique data set comprising a ten-year time series of orchard-specific hail damage and hail insurance data is used.

For orchards with low local hail risk and low yield potential, not using hail risk mitigation is most efficient. For orchards with high local hail risk and high yield potential, anti-hail nets provide the highest certainty equivalents. For orchards with high local risk, but low yield potential, hail insurance is most efficient. For orchards, with low local risk, but high yield potential, the certainty equivalents are higher for anti-hail net, when the farmer is risk neutral or slightly risk-averse. With increasing risk aversion, hail insurance is most efficient, which can be explained by the greater degree of the instrument’s flexibility.

The novelty of the study lies in the direct comparison of the risk effects of anti-hail nets and hail insurance in fruit production.

Hailstorms are a major risk in agriculture. In order to mitigate the negative consequences on farm revenues, in the present paper the authors analyse the choice between insurance contracts and anti-hail nets. Furthermore, the authors discuss the consequences of anti-hail nets adoption on the actuarial soundness of the insurance market.

In this paper the authors firstly develop a theoretical model based on expected utility theory to compare the profitability of no-hedging against insurance and anti-hail nets. Subsequently, they test their theoretical model predictions with data of South Tyrolean apple producers.

The authors find that the benefit of anti-hail nets compared to insurance is an increasing function of the overall risk of hail damages, of the farmers' level of risk aversion and of the worth of the agricultural output.

Given the authors’ findings that anti-hail nets are more profitable for riskier, risk-averse and high-profitable farmers, the diffusion of anti-hail nets could be beneficial for the actuarial soundness of insurance markets.

The model developed in the paper is specifically designed to compare the profitability of different agricultural hedging options and can be easily extended to cover other hazards.

Climate change is expected to cause larger and more frequent precipitation events in key agricultural regions of the United States, damaging crops and soils. Subsurface tile drainage is an important technology for mitigating the risks of a wetter climate in crop production. In this study, the authors examine how quickly farmers adapt to increased precipitation by investing in drainage technology.

Using farm-level data from the 2018 Agricultural Resource Management Survey (ARMS) of soybean producers, the authors construct a drainage adoption timeline based on when the operator began farming their land and when tile drainage was installed, if at all. The authors examine both the initial investment decision and the speed with which drainage is installed by adopters. A Heckman-style Poisson regression is used to model the count nature of adoption speed (measured in years taken to install tile drainage) and to correct for potential sample-selection bias.

The authors find that local precipitation is not a significant determinant of the drainage investment decision but may be highly influential in the timing of adoption among drainage users. Farms exposed to crop-damaging levels of precipitation install tile drainage faster than those with low to moderate levels of rainfall. Estimates of farm adaptation speeds are heterogeneous across farm and operator characteristics, most notably land tenure status.

Understanding how US farmers adapt to extreme weather through technology adoption is key to predicting the long-term impacts of climate change on America's food system. This study extends the existing climate adaptation literature by focusing on the speed of adoption of an important and increasingly common climate-mitigating technology – subsurface tile drainage.

Children and young people’s time is generally structured by adults’ ideas and interests, be it in the family (sleeping or eating times), in the social world (time of school) or in the cultural realm (holidays and festivities). Children’s autonomy of how they spend their time is reduced to certain spaces, which again are assigned to them by adults. For the past two decades, digital media has entered many people’s – adults as well as children’s and young people’s – everyday life.

With the omnipresent and growing use of digital media by young people – fueled even more by mobile devices – grows a discourse around possible (negative) effects and supposedly necessary pedagogical monitoring and restrictions of their digital media time.

These discussions regarding negative effects on well-being and school performance include formal recommendations for limiting the quantity of time spent online. Hereby, mainly the digital time outside school is addressed and potentially problematized. Despite numerous studies on the effects of digital media time on different aspects of young people’s lives there is little research asking for children’s and young people’s perspectives on digital media use and time.

This study uses questionnaires (509) and qualitative interviews (15) to explore young people’s perspectives in terms of meaning, quality and quantity of the time spent with digital media. The participants were youth aged 12–20 from northern Germany. Using qualitative content analysis, findings point to a necessary differentiation between the purpose of usage, respective effects and evaluations.

Accordingly, being online can be an act (a) of self-actualization including positive effects creating great meaning for well-being, identity and appropriation of the digital world for their own future, (b) a waste of time when, for example, using social media or gaming to pass the time including a feeling that time is accelerated and rushing, personal regrets and references to loss of control and the need for self-control, and (c) a pragmatic naturalization of the digital as one part of life for various individual or social purposes and developments.

The article discusses young people’s evaluations and perspectives addressing the possibly artificial adult differentiation of analog and digital time or activities as well as adults’ presumptions about young people’s digital time and the strive for control resulting from these. Additionally, insights from the circumstances of the COVID-19 lockdown are included in gaining knowledge about what is actually important and rewarding when young people spend time digitally. The chapter aims at an intergenerational understanding of the significance of digital media in young people’s lives questioning alarmist scenarios of a generation that is lost in the digital world.

The paper aims to analyze the structural integrity of an existing offshore platform located in the Northern Adriatic Sea, followed by the topside decommissioning and the re-utilization of the jacket as a wind turbine support. The structural integrity assessment against the in-place and the long-term actions is accomplished by using a reduced basis finite element method (RB-FEA) software program assessing the capability of the jacket to be used as a support for wind turbines at the end of its life cycle as oil and gas (O&G) platform.

The project starts by modeling the jacket, and subsequently, the structural analyses for the in-place loads in operative and extreme conditions are performed. Then, the fatigue analysis is carried out in order to define the cumulative damage necessary to evaluate the possibility to use the jacket as a wind turbine support.

The results show that the jacket, at the end of the service life as O&G platform, is able to withstand the loads produced by the installation of the wind turbine since the analyses are satisfied even with the conservative approach used which overestimates the thickness loss assuming a linear increasing value during the service life.

Because of the chosen approach, the study presents some limitations, especially concerning the real state of the platform which has been defined considering the thickness loss only. Additionally, a 1D model was used to perform the analyses, and hence, a 3D model could help in evaluating the critical points with higher precision.

The assessment of the structure could be improved by modeling a digital twin of the asset allowing a real-time monitoring which, however, involves a huge amount of data to be processed, so a suitable simulation technology must be used.

The RB-FEA proposed by Akselos is suitable to perform the analyses speeding up the processing of the data even in real time.