GENERALIZED FORCES AND DISSIPATION FUNCTIONS IN THE CONTEXT OF AN INTERNAL VARIABLE APPROACH APPLIED TO THE SOLUTION OF ELASTIC-PLASTIC PROBLEMS

A non-traditional approach to the numerical analysis of elastic-plastic systems is discussed by focusing on a formulation that makes use of internal variables and dissipation functions. These functions are used in order to enforce the constitutive law, so that they play the role of the yield functions in the framework of the classical theory of plasticity. With reference to finite element discrete models, it is shown that the solution of an elastic-plastic problem corresponds to the minimum point of a convex function (when the material is stable in Drucker\u2019s sense) and that convergence is guaranteed when a convenient time integration method (usually known as backward-difference scheme) is applied. As a matter of fact, it can be proved that the value of that function progressively decreases (iteration by iteration) when a proper time integration strategy is implemented. Elastic-plastic systems will be considered, which are subjected to uniaxial and multiaxial stress states (by assuming Mises\u2019 yield condition for two-dimensional and three-dimensional finite elements). In all cases, it will be easily noticed that the dissipation functions depend on convenient generalized forces, whose features are obvious in the presence of uniaxial stress states. Instead, when the structural system is subjected to multiaxial stress states, the actual meaning of the generalized forces must be properly understood in order to define convenient dissipation functions and/or yield functions: this is the main issue of the present paper and represents a topic which, to the authors\u2019 knowledge, has not been adequately investigated, yet

Reliability criteria for re-engineering of large-scale pressurized irrigation systems

Presented during the Third international conference on irrigation and drainage held March 30 - April 2, 2005 in San Diego, California. The theme of the conference was "Water district management and governance."Includes bibliographical references.A study was conducted in a pressurized irrigation district in southern Italy to analyze current delivery performance and determine improvements needed to meet current and future delivery needs. Such an analysis is required due to changes that have occurred, since the system was first put into service, in cropping patterns, farming practices and irrigation techniques. The Combined Optimization and Performance Analysis Model (COPAM) was used to evaluate the irrigation system present performance under different operating conditions, to identify the areas within the irrigation district where rehabilitation and modernization are more urgently needed, and to suggest the most effective engineering and operational improvements. Post-intervention operating scenarios were simulated and analyzed to refine and validate the re-engineering process. Results show the usefulness of simulation models when analyzing modernization alternatives for irrigation schemes.Sponsored by USCID; co-sponsored by Association of California Water Agencies and International Network for Participatory Irrigation Management

An Iterative Procedure for the Analysis of Nonlinear Elastic Systems Subjected to Uniaxial Loading and Large Displacements

The paper deals with an iterative procedure for the solution of elastic problems, for which the large displacement theory must be considered. It is shown that the algorithm, based upon a non-traditional iterative scheme, tends to converge to the correct solution and some numerical tests are considered, by assuming a linear and piecewise-linear material model

Environmental sustainability

Presented at Ground water and surface water under stress: competition, interaction, solutions: a USCID water management conference on October 25-28, 2006 in Boise, Idaho.Includes bibliographical references.A study was conducted on a large-scale irrigated area located in southern Italy to analyze the cumulative effects of long-term water management practices on soils and aquifers. Assessing the environmental sustainability of irrigation systems operations was the main goal of the present research. This included envisaging feasible changes to "business-as-usual" in the study area with the aim of reducing pressures and of meeting current and future management objectives. The Determinants-Pressure-State-Impact-Response methodology suggested by the European Environmental Agency was applied to the case study to analyze cause-effect relationships between driving forces, pressures and potential impacts. Simulations of alternatives in water management and evaluation of resulting consequences were conducted by developing a spatial Decision Support System (DSS) on the study area. This basically involved development and ranking of alternatives by using a commercial software package (DEFINITE DSS). Evaluation of the most likely resulting consequences was conducted by creating maps of environmental risk by means of two commercial GIS software packages (ArcGIS and IDRISI). The used approach showed its usefulness for achieving better understanding of relevant aspects related to management of irrigation water at regional scale, for designing strategic monitoring programs to be implemented and for envisaging feasible management alternatives on large-scale irrigation systems

Improving water-efficient irrigation: prospects and difficulties of innovative practices

Innovative irrigation practices can enhance water efficiency, gaining an economic advantage while also reducing environmental burdens. In some cases the necessary knowledge has been provided by extension services, helping farmers to adapt and implement viable solutions, thus gaining more benefits from irrigation technology. Often investment in technological improvements has incurred higher water prices, however, without gaining the full potential benefits through water efficiency. Farmers generally lack adequate means and incentives to know crops’ water use, actual irrigation applications, crops’ yield response to different water management practices, and thus current on-farm water-efficiency levels. Those general difficulties are illustrated by our two case studies investigating options, stimuli and difficulties to improve water-efficient practices. The two areas have strong stimuli for improvement but lack a knowledge-exchange system to help farmers and resource managers identify scope for improvements. Partly for this reason, farmers’ responsibility for efficient water management has been displaced to hypothetical prospects, e.g. extra supplies from reuse of treated wastewater or a long-term low water pricing. In both cases a displaced responsibility complements the default assumption that farmers’ irrigation practices already have adequate water-use efficiency. Under current circumstances, agricultural water management will maintain the unknown water-efficiency level and farmers will have weaker incentives to make efforts for more efficient practices. A continuous knowledge-exchange is necessary so that all relevant stakeholders can share greater responsibility across the entire water-supply chain. On this basis, more water-efficient management could combine wider environmental benefits with economic advantage for farmers

Site characteristics determine the effectiveness of tillage and cover crops on the net ecosystem carbon balance in California vineyard agroecosystems

Globally, wine grape vineyards cover approximately 7.4 M ha. The potential for carbon (C) storage in vineyards is of great interest to offset greenhouse gas emissions and mitigate the effects of climate change. Sustainable soil management practices such as cover crop adoption and reduced tillage may contribute to soil organic carbon (SOC) sequestration. However, site-specific factors such as soil texture, other soil physicochemical properties, and climate largely influence the range and rate to which SOC may be stored. To measure the potential for C storage in vineyards under varying sustainable soil management practices, we calculated the net ecosystem carbon balance (NECB) of three cover crops [perennial grass (Poa bulbosa hybrid cv. Oakville Blue); annual grass (barley, Hordeum vulgare); resident vegetation (natural weed population)] under conventional tillage (CT) and no-till (NT) management. Results provided evidence that vineyards served as C sinks. In sandy soils, the type of cover crop and tillage may be of little influence on the NECB. While in finer-textured soils, tillage reduced the NECB and higher biomass-producing cover crops enhanced the overall C storage potential of the vineyard agroecosystem. Overall, our results revealed that site characteristics, namely, soil texture and climate, were key determinants of the C storage potential of vineyards in Mediterranean climates such as those found in coastal and inland California wine grape production regions

Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis

Multiple Sclerosis (MS) progresses at an unpredictable rate, but predictions on the disease course in each patient would be extremely useful to tailor therapy to the individual needs. We explore different machine learning (ML) approaches to predict whether a patient will shift from the initial Relapsing-Remitting (RR) to the Secondary Progressive (SP) form of the disease, using only “real world” data available in clinical routine. The clinical records of 1624 outpatients (207 in the SP phase) attending the MS service of Sant'Andrea hospital, Rome, Italy, were used. Predictions at 180, 360 or 720 days from the last visit were obtained considering either the data of the last available visit (Visit-Oriented setting), comparing four classical ML methods (Random Forest, Support Vector Machine, K-Nearest Neighbours and AdaBoost) or the whole clinical history of each patient (History-Oriented setting), using a Recurrent Neural Network model, specifically designed for historical data. Missing values were handled by removing either all clinical records presenting at least one missing parameter (Feature-saving approach) or the 3 clinical parameters which contained missing values (Record-saving approach). The performances of the classifiers were rated using common indicators, such as Recall (or Sensitivity) and Precision (or Positive predictive value). In the visit-oriented setting, the Record-saving approach yielded Recall values from 70% to 100%, but low Precision (5% to 10%), which however increased to 50% when considering only predictions for which the model returned a probability above a given “confidence threshold”. For the History-oriented setting, both indicators increased as prediction time lengthened, reaching values of 67% (Recall) and 42% (Precision) at 720 days. We show how “real world” data can be effectively used to forecast the evolution of MS, leading to high Recall values and propose innovative approaches to improve Precision towards clinically useful values