Extrinsic modeling and simulation of helio-photovoltaic system: a case of single diode model

Simulation of helio-photovoltaic system is continuously undergoing revolution through diverse parameter modifications which closely mimic the experimental data. In retrospect, the current work has presented a nonlinear modification of equivalent circuit parameters and simulated the same for different semiconductors (crystalline and thin films); furthermore, established a mathematical relation between the coefficients of solar irradiance and module temperature (SIMT); moreover, investigated the influence of SIMT on the model parameters. The simulation upshot reveals that increment in solar irradiance (SI) intensifies the output current whereas an increase in module temperature (MT) diminishes the output voltage; the SIMT coefficients developed validated well with the manufacturers data; the influence of SI was evident on the photon current, diode current, and shunt resistance whereas the effect of MT was pronounced on the diode current, ideality factor, and shunt resistance. Thus, the provision made by this work is essential for advanced design and simulation of helio-photovoltaic systems.     

Toward Cyborg PPGIS: exploring socio-technical requirements for the use of web-based PPGIS in two municipal planning cases,Stockholm region,Sweden

Web-based Public Participation Geographic Information Systems (PPGIS) are increasingly used for surveying place values and informing municipal planning in contexts of urban densification. However, research is lagging behind the rapid deployment of PPGIS applications. Some of the main opportunities and challenges for the uptake and implementation of web-based PPGIS are derived from a literature review and two case studies dealing with municipal planning for urban densification in the Stockholm region, Sweden. A simple clustering analysis identified three interconnected themes that together determine the performance of PPGIS: (i) tool design and affordances; (ii) organisational capacity; and (iii) governance. The results of the case studies augment existing literature regarding the connections between the different socio-technical dimensions for the design, implementation and evaluation of PPGIS applications in municipal planning. A cyborg approach to PPGIS is then proposed to improve the theoretical basis for addressing these dimensions together.     

Experimental investigation,intelligent modeling and multi-characteristics optimization of dry WEDM process of Al–SiC metal matrix composite

Dry wire electrical discharge machining (WEDM) is an environmentally friendly modification of the oil WEDM process in which liquid dielectric is replaced by a gaseous medium. In the present work, parametric analysis has been fulfilled while dry WEDM of Al–SiC metal matrix composite. Experiments were designed and conducted based on L₂₇ Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Firstly, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on the values of cutting velocity. After selection of best gas and best wire, they were used for later stage of experiments. Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, an adaptive neuro-fuzzy inference system (ANFIS) has been employed to predict the process characteristics based on experimental observation. At the end, an artificial bee colony (ABC) algorithm has been associated with ANFIS models to maximize CV and minimize SR, simultaneously. Then the optimal solutions that obtained through ANFIS-ABC technique have been compared with numbers of confirmatory experiments. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also, according to ANOVA, pulse on time and discharge current were found to have significant effect on CV and SR. In modeling of CV and SR by ANFIS, it was resulted that the proposed method has superiority in prediction of them in the ranges of factors beyond the training condition. Also, association of ANFIS with ABC can find the optimal combination of process parameters accurately according to the confirmatory experiments.     

Promoting ecological sustainable planning for natural stone quarrying. The case of the Orosei Marble Producing Area in Eastern Sardinia

This paper presents an analysis of the main environmental impact factors (noise, vibration, fumes, dust, vehicle traffic) associated with marble quarrying and processing in the Orosei industrial area and their effects. Solutions are also proposed to prevent, mitigate and, where possible, eliminate the impact on the environment. Using three-dimensional topographic models, the authors simulated quarry and industrial processing development, with projections over the next 10, 30 and 50 years. The aim of these simulations was to establish land management planning guidelines for the optimal and environmentally sustainable development of the Orosei Marble industrial area. Lastly, careful quarry development planning is important both for enhancing LCA and for improving production processes through sustainable technologies that yield green label products meeting environmental performance standards.     

A provider-based water planning and management model--WaterSim 4.0--for the Phoenix Metropolitan Area

Uncertainty in future water supplies for the Phoenix Metropolitan Area (Phoenix) are exacerbated by the near certainty of increased, future water demands; water demand may increase eightfold or more by 2030 for some communities. We developed a provider-based water management and planning model for Phoenix termed WaterSim 4.0. The model combines a FORTRAN library with Microsoft C# to simulate the spatial and temporal dynamics of current and projected future water supply and demand as influenced by population demographics, climatic uncertainty, and groundwater availability. This paper describes model development and rationale. Water providers receive surface water, groundwater, or both depending on their portfolio. Runoff from two riverine systems supplies surface water to Phoenix while three alluvial layers that underlie the area provide groundwater. Water demand was estimated using two approaches. One approach used residential density, population projections, water duties, and acreage. A second approach used per capita water consumption and separate population growth estimates. Simulated estimates of initial groundwater for each provider were obtained as outputs from the Arizona Department of Water Resources (ADWR) Salt River Valley groundwater flow model (GFM). We compared simulated estimates of water storage with empirical estimates for modeled reservoirs as a test of model performance. In simulations we modified runoff by 80%-110% of the historical estimates, in 5% intervals, to examine provider-specific responses to altered surface water availability for 33 large water providers over a 25-year period (2010-2035). Two metrics were used to differentiate their response: (1) we examined groundwater reliance (GWR; that proportion of a providers' portfolio dependent upon groundwater) from the runoff sensitivity analysis, and (2) we used 100% of the historical runoff simulations to examine the cumulative groundwater withdrawals for each provider. Four groups of water providers were identified, and discussed. Water portfolios most reliant on Colorado River water may be most sensitive to potential reductions in surface water supplies. Groundwater depletions were greatest for communities who were either 100% dependent upon groundwater (urban periphery), or nearly so, coupled with high water demand projections. On-going model development includes linking WaterSim 4.0 to the GFM in order to more precisely model provider-specific estimates of groundwater, and provider-based policy options that will enable "what-if" scenarios to examine policy trade-offs and long-term sustainability of water portfolios.     

Passive and active adaptive management: approaches and an example

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.     

Adaptive management of natural resources--framework and issues

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.     

Calculating ecological carrying capacity of shellfish aquaculture using mass-balance modeling: Narragansett Bay, Rhode Island

Increasing growth in the aquaculture industry demands ecosystem-based techniques for management if that growth is to be ecologically sustainable and promote equity among users of the ecosystems in which it occurs. Models of carrying capacity can be used to responsibly limit the growth of aquaculture in increasingly crowded coastal areas. Narragansett Bay, Rhode Island, USA is one such crowded coastal region experiencing a rapid increase in bivalve aquaculture. An ecosystem mass-balance model was used to calculate the ecological carrying capacity of bivalve aquaculture. Cultured oyster biomass is currently at 0.47 t km⁻² and could be increased 625 times without exceeding the ecological carrying capacity of 297 t km⁻². This translates to approximately 38,950 t of harvested cultured oysters annually which is 4 times the total estimated annual harvest of finfish. This potential for growth is due to the high primary productivity and large energy throughput to detritus of this ecosystem. Shellfish aquaculture has potential for continued growth and is unlikely to become food limited due, in part, to the large detritus pool.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

Ecosystems emerging. 5: Constraints

Ecosystem constraints are both ontic and epistemic. They limit activity, and as problems to be solved they drive organization, which is our hypothesis:

The driver of organization is constraint.

Solutions proliferate further constraints in an unending spiral of problem (constraint) generation and solution. As constraints proliferate, behavior narrows, and species diversify to compensate (paradox of constraint). Resource enrichment reduces constraints, releases behavior, and reduction of challenges decreases diversity (paradox of enrichment)—high diversity is expressed in low-resource environments and low diversity in high-resource environments. A three-part model of constraints is formulated for non-living systems, and also for goal-directed, problem-solving biota. Mode 1: dynamical means behavior is co-determined by internal states and external inputs. Mode 2: cybernetic employs negative feedback to keep dynamics within goal-oriented operating limits. Mode 3: model-making entails ability to represent (model) physical reality and respond to both phenomenal (modeled) and physical inputs; this property distinguishes living from nonliving systems. Principal sections of the paper elaborate dynamical constraints (three classes), boundary constraints (expressed in edge effects and trophic dynamics), physical constraints (space, time, temperature), chemical constraints (environment fitness, ecological stoichiometry, chemical evolution, limiting factors), coding constraints (environmental vs. genetic coding), network and pathway constraints (connectivity), and natural selection constraints (fitting to the biosphere). Consideration of how the world would look without constraints suggests how fundamental these are in ecosystem emergence, and how the next property in this series, differentiation, would be unmotivated without them. We conclude that constraints as a category are under-studied in ecology, poorly understood in ecological phenomenology, and (our hypothesis) comprise a ubiquitous organizing force in nature.