Characterization of Commercial Polyvinylbutyrals Corroyer, Elsa; Brochier-Salon, Marie-Christine; Chaussy, Didier ...
International journal of polymer analysis & characterization,
07/2013, Letnik:
18, Številka:
5
Journal Article
Recenzirano
Several analyses have been carried out to thoroughly characterize five commercial polyvinyl butyral films supplied by various manufacturers. Model compounds (PVB and plasticizers) having the highest ...purity available were also used as reference. FT-IR and
1
H- and
13
C-NMR spectroscopy were used to ascertain the structure of the investigated ter-polymer, as well that of the incorporated additives (mainly the plasticizer). The ratio between these components was also determined. The chemical compositions of these PVBs were similar, and two different plasticizers were identified. The glass transition temperature (T
g
) was deduced from dynamic mechanical analyses (DMA) and found to be very similar for all the investigated films. Size exclusion chromatography (SEC) was also used to study the molecular weight distribution. The analyses were performed using several detectors, and they revealed that PVBs presented similar distributions with molecular weights ranging from 250,000 to 300,000 g/mol.
Evaluation of the wear resistance for tools and dies, particularly for coated components, is a challenging task in surface engineering testing. Pin‐on‐disc is a widely employed method in the ...literature; its result is rather associated with the friction aspect of the samples than wear resistance for components. A microabrasive test has been suggested recently to assess the wear resistance of hard coatings. The key point in that is to simulate the aspect which is close to the factor of the industrial performance for most of the components. This paper aims to compare pin‐on‐disc tests and microabrasive methods. Two hard coatings of CrN and CrSiN were deposited using a closed field unbalanced magnetron sputter ion plating system. SiC was used as the abrasive particle in the slurry. Results show that the abrasive wear rates of the CrN coatings changed sensitively with the depositing parameters. At the same time, the specific wear rate from pin‐on‐disc test was not able to pick up the change of wear endurance of the coatings. A hole drilling test indicates that the number of holes increases significantly when the abrasive wear rate is lower than a certain critical value. It is concluded that the microabrasive test is an appreciable method in practice to evaluate the wear resistance of hard coatings.
•A model simulating the water stress dynamics of bi-specific agrosystems is proposed.•Dedicated modelling concepts were used to provide genericity and to limit input parameters.•The model was tested ...on salads, mono/bispecific vineyards and peach orchards.•RMSE of the water stress index ranged from 0.049 to 0.123.•BISWAT model can contribute to the design of new agro-ecological cropping systems.
The ability to simulate soil and crop processes in many bi-specific systems (vineyards, orchards, silvo-arable agroforestry, strip-intercropping of arable crops…) is one of the major challenge for crop modelling in order to contribute to the design of agro-ecological cropping systems. A typical question is how soil, climate and management would influence the soil water deficit experienced by a plant grown alone or intercropped with a cover crop, with another crop or a tree, in order to improve the resilience of a cropping system to climate change and limit the use of chemical input.
This study introduces BISWAT – Bispecific Intercrop System WATer Stress dynamic model - a new water balance model designed to simulate the dynamic of Soil Water deficit Experienced (SWEP) by two Plants when grown together or separated. BISWAT has been built to simulate a large range of agrosystems (annual and perennial crops, mono- or bi-specific) cultivated in various conditions. The model is primarily based on three modelling concepts: i) a 2D generic pattern for the system’s spatial representation, ii) the use of the Radiation Interception Efficiency (RIE) to drive potential plant transpiration and soil evaporation, iii) the use of the Total Transpirable Soil Water (TTSW) concept coupled with a simple root dynamics representation. These concepts are not new but they allowed us to define a model able to simulate many crops and trees (including vineyards) using a limited number of inputs and without an explicit need for parameter calibration.
The model was evaluated on five reference agrosystems (mono-specific salads, mono-specific vineyards, bi-specific vineyards, mono-specific peach orchards and bi-specific peach orchards). The RMSE of the SWEP variable ranged from 0.049 to 0.123. A combined sensitivity and uncertainty analysis performed on typical farmer’s fields situations stressed the particular importance of model inputs related to the TTSW of the soil-crop system.
We conclude that the genericity of the BISWAT model, its method of parameterization and its performance open the perspective to use the model in a wide range of conditions where the dynamic of water stress between two species grown together is a key variable to be accessed with limited data for parameterization and a large number of fields to simulate.
► We describe a protocol for the conceptual modelling of an agro-ecosystem (CMA). ► The method is illustrated and discussed using three case studies to show how the CMA can be used to build a ...systemic representation of a complex agro-ecosystem, to guide agronomic diagnosis and yield gap analysis, and to elicit expert knowledge for the design of field experiments. ► Thanks to its modularity and transparency, CMA can be shared among disciplines, re-used and updated. ► We discuss the CMA's normative aspects, its representation and links with numerical modelling.
Innovative agricultural systems need to combine the production of goods with the provision of environmental services. When agronomists analyse or design multifunctional agro-ecosystems, they thus need to include knowledge of an increasing range of scientific disciplines (plant biology, soil science, ecology, etc.) while continuing to use their systemic approach as a cornerstone. Increasing amounts of knowledge of different types (concepts and data) will thus have to be included in systemic approaches that are developed in the agronomic domain. Knowledge integration and sharing are frequently hampered by the lack of detail in the assumptions made in each discipline. We hypothesise that a standardised description of the conceptual model underlying data collection and the analysis of agro ecosystems would improve transparency and knowledge integration.
Here we propose a protocol to formalise the conceptual modelling of an agro-ecosystem (CMA) related to a specific agronomic issue. The CMA protocol is implemented in four iterative steps: (i) structural analysis, (ii) functional analysis, (iii) dynamic analysis, and (iv) consistency check. The final product is a conceptual model of an agro-ecosystem whose key elements are a structured knowledge base and associated graphical representations. The protocol was drawn up based on three case studies concerning three different biophysical objects (coffee agroforest, cotton, grapevine) with different problems to be addressed. They are given here as an illustration of how to apply the CMA protocol, and to show how it can be used as a tool to build a systemic representation of a complex agro-ecosystem, as a tool for agronomic diagnosis and yield gap analysis, or as a tool to elicit a range of expert knowledge to design new field experiments.
The CMA protocol proved to be efficient in guiding the process of conceptualisation up to the point at which the variables that need to be measured in the field are identified and interlinked. It enabled elicitation and integration of knowledge from different biophysical disciplines and different types of expertise during the conceptualisation process. It also enabled identification of knowledge gaps, and the design and analysis of experiments to tackle complex problems. The CMA yielded by the protocol could be used again, thanks to its transparency and modularity. Further work is underway to improve the CMA representation and its uses in numerical model specification and in participatory methods for the design of cropping systems.
Dynamic crop simulation models are widely used to investigate, through virtual experiments, the response of crop yield to changes in climate, management or crop genetic traits. In a search for ...widespread applicability, crop models include a large number of processes, sometimes to the detriment of their mathematical transparency.
Simulated crop yield responses to variation in model inputs result from the integration over a long period (one or several years) of many different crop processes interacting at the model time-step, typically the day. Thus, by definition, yield explanatory factors are intricate and difficult to link efficiently to the crop processes. Ranking their relative contributions to the final yield output is for example almost impossible.
In this work, we introduce a new approach to understand the response of crop yield Y by comparing two simulation runs (computing two yields Y1 and Y2) of the same model and by focussing on the relative yield: y = Y1/Y2. Providing that the mathematical formulation of the dynamic crop model verifies simple hypotheses held by most crop models, we show that it is possible to factorise the relative yield y into several terms. These terms can be (i) interpreted as the specific effects of the modelled crop processes on the crop yield, (ii) compared to rank the effects of the crop processes on the crop yield. Their definition involves using state variables of the model computed during the simulation runs. The method does not involve running the model numerous times, neither changing its formulation. It may require to output new variables that are not in the set of variables proposed by the released version of the model. We call our method the relative yield decomposition (RYD) method.
We illustrate how the RYD provides insight in the analysis of complex crop models by applying it to two models: Yield-SAFE (agroforestry model) and STICS (crop model). The method allows to identify and quantify the importance of the main processes responsible for crop yield variations for different simulation configurations in the two models.
The relative yield decomposition method is complementary to other model analysis methods like sensitivity analysis or multiple model simulations. We show that it could be applied to some widely used crop models (e.g. AQUACROP, CERES, CROPGRO, CROPSYST, EPIC, SIRIUS, SUCROS). The relative yield decomposition method appears as a powerful and generic tool to analyse the behaviour of complex crop models that can help to improve the formulation of the models, or even to study specific plant traits or crop processes when applied to a model accurate enough.
•We introduce a method to analyse the results of crop models.•The method is based on a mathematical decomposition of the relative yield.•The decomposition allows to rank the effects of the different crop processes.•The method is illustrated on two crop models.
The “Use and Abuse of Crop Simulation Models” special issue of Agronomy Journal published in 1996 ended with the myth of the universal crop model. Sinclair and Seligman consequently recommended ...tailoring models to specific problems. This paper reviews the fate of the idea of such ad hoc approaches to crop simulation modeling during the past 15 yr. Most crop modelers have since adhered to the principles formulated by Sinclair and Seligman, but yet their practice faces two major issues: (i) how to define the structure of the model as depending on the question to be addressed (model conceptualization) and (ii) how to minimize efforts in software development (model computerization). Progress in model conceptualization as reported in the literature concerns (i) inferring a conceptual model from what is known of the problem to address, (ii) deriving summary models from comprehensive ones, and (iii) using multivariate methods to analyze the hierarchy of drivers of variability in the variable to be predicted. Considerable effort has been invested in the development of frameworks to facilitate model computerization, and the commercial modeling software is constantly improving. But there are limits in the flexibility permitted by these tools. Acquiring basic skills in coding a model using a scientific programming language is preferred by scientists wishing to keep the fullest understanding and control on their crop models. Connecting the model to commercial database software may facilitate this strategy. However, the computerization issue may still lead to tensions between modeling teams concerning the legitimacy to develop their own model.
Achieving consistency between agricultural diversification and food diversity is no easy task, as it calls into question, beyond farming systems strategy, the organization of supply chains and ...agricultural landscapes, and the distribution of value within the production-food industry-distribution chain. But changes are underway to meet societal demands for agro-ecological transition and food transition, for which diversification is a pillar, with numerous experiments, in research and development and in partnership actions. Even if a number of hurdles still need to be overcome, we are well on the way to making agricultural diversity and food diversity consistent with each other. In conclusion we suggest some avenues to explore.
Mettre en cohérence la diversification des productions agricoles et la diversité alimentaire ne va pas de soi car cela remet en question, au-delà des stratégies des exploitations agricoles, l’organisation des filières et des territoires et la répartition de la valeur au sein de la chaîne production-transformationdistribution. Mais des changements sont à l’œuvre pour répondre aux demandes sociétales de transition agroécologique et de transition alimentaire dont la diversification est un pilier, avec de nombreuses expériences, dans la recherche-développement et dans des actions en partenariat. Même s’il faudra encore lever un certain nombre de verrous, la mise en cohérence entre diversité agricole et diversité alimentaire est en chemin et nous donnons en conclusion quelques pistes à creuser.
Innovative agricultural systems need to combine the production of goods with the provision of environmental services. When agronomists analyse or design multifunctional agro-ecosystems, they thus ...need to include knowledge of an increasing range of scientific disciplines (plant biology, soil science, ecology, etc.) while continuing to use their systemic approach as a cornerstone. Increasing amounts of knowledge of different types (concepts and data) will thus have to be included in systemic approaches that are developed in the agronomic domain. Knowledge integration and sharing are frequently hampered by the lack of detail in the assumptions made in each discipline. We hypothesise that a standardised description of the conceptual model underlying data collection and the analysis of agro ecosystems would improve transparency and knowledge integration. Here we propose a protocol to formalise the conceptual modelling of an agro-ecosystem (CMA) related to a specific agronomic issue. The CMA protocol is implemented in four iterative steps: (i) structural analysis, (ii) functional analysis, (iii) dynamic analysis, and (iv) consistency check. The final product is a conceptual model of an agro-ecosystem whose key elements are a structured knowledge base and associated graphical representations. The protocol was drawn up based on three case studies concerning three different biophysical objects (coffee agroforest, cotton, grapevine) with different problems to be addressed. They are given here as an illustration of how to apply the CMA protocol, and to show how it can be used as a tool to build a systemic representation of a complex agro-ecosystem, as a tool for agronomic diagnosis and yield gap analysis, or as a tool to elicit a range of expert knowledge to design new field experiments. The CMA protocol proved to be efficient in guiding the process of conceptualisation up to the point at which the variables that need to be measured in the field are identified and interlinked. It enabled elicitation and integration of knowledge from different biophysical disciplines and different types of expertise during the conceptualisation process. It also enabled identification of knowledge gaps, and the design and analysis of experiments to tackle complex problems. The CMA yielded by the protocol could be used again, thanks to its transparency and modularity. Further work is underway to improve the CMA representation and its uses in numerical model specification and in participatory methods for the design of cropping systems.
This Preliminary Design Report (PDR) describes the IsoDAR electron-antineutrino source. Volumes I and II are site-independent and describe the cyclotron driver providing a 10~mA proton beam, and the ...medium energy beam transport line and target, respectively. Volume III describes the installation at the Yemilab underground laboratory in South Korea. The IsoDAR driver and target will produce a mole of electron-antineutrinos over the course of five years. Paired with a kton-scale liquid scintillator detector, it will enable an impressive particle physics program including searches for new symmetries, new interactions and new particles. Here in Volume I, we describe the driver, which includes the ion source, low energy beam transport, and cyclotron. The latter features radiofrequency quadrupole (RFQ) direct axial injection and represents the first accelerator purpose-built to make use of vortex motion.