The toughness of SWCNT was estimated to be 770 J/g and MWCNT to be 1270 J/g. As a carbon allotrope, CNT like diamond and graphite is a very good conductor of heat. However, due to technological shortcomings associated with experimental measurements on a nanoscale, the direct and quantitative measurements of thermal conductivity of CNT individually is yet to be achieved. Hence, the thermal conductivities obtained so far has been due to experiments and computational simulations with significantly scattered results ranging between 2000 and 6000 W/m-K. The thermal conductivity depends on the atomic arrangement, geometric parameters such as diameter and length of the tube, structural defects on the surface of the CNT and impurities within them. Transport of thermal energy within the CNT is assumed to occur through phononconduction mechanism, a mechanism common amongst non-metallic materials. The phonon conduction mechanism is influenced by parameters such as number of phonon active nodes, boundary surface scattering, the length of the free mean path for the phonons and inelastic Umklapp scattering. For this study, MWCNT is dispersed in a polymer matrix of Reactive Ethylene Terpolymer to study photomechanical actuation. RET is composed of 3 monomers namely, polyethylene, a methylmethacrylate group, and epoxide group. Polyethylene and methyl-methacrylate groups contribute elastomeric properties and corrosion resistance. Ethylene group helps in physical cross-linking by forming crystalline domains. The two groups are vital for hot melt adhesive and coating applications. In the presence of CNTs with functional groups such as -OH, -COOH etc. the epoxide group forms ring bonds and provides anchoring.
The physical properties of RET are provided in table 2 and the physical structure is depicted in figure 3. At the core, both ultrasonic bath and probe work similarly,10 liter drainage pot by the sequence of bubble nucleation and collapse. The ultrasonic bath contains, usually, a rectangular bath where the solution to be dispersed is kept in a water bath. The ultrasonic energy is transmitted through water across the walls of the bath which affects the solution uniformly. Water should be maintained at the same level as the solution. In probe sonication, the probe, oscillating at a controlled frequency, is dipped in the solution to impart sonic energy. The oscillation of the probe tip initiates the formation of bubbles which results in cavitation due to its implosion, providing the energy for dispersion. The tip of the probe is usually given a small taper to focus its intensity. Sonication takes place because of bubble nucleation and collapse. This process is called acoustic cavitation. The rapidly oscillating bath/probe tip produces a field of high energy, resulting in bubble formation. The bubble, thus formed, separates the entangled CNTs as the bubble grows. When the bubble implodes, the energy released causes dispersion. On certain instances, the energy released is high enough to fragment CNT. During implosion, the time is just sufficient for the solution to diffuse into the opened gap within the boundary of the bubble. The repeated cavitation process, along the length of the CNTs, helps the solution to penetrate and percolate between the tubes. Between the bath and probe, probe produces more defined cavitation zone and hence produces more localized energy than the bath. A noteworthy observation is that the size of the bubbles thus produced is inversely proportional to the frequency of ultrasound.
Likewise, the energy released is higher in the case of the implosion of larger bubbles formed due to lower frequencies. Hence, as the frequency is increased, nucleation and cavitation diminishes. It ceases altogether at frequencies higher than 2.5 MHz. The California Energy Commission Public Interest Energy Research 2010 Climate Change Vulnerability and Adaptation study includes the development of down scaled climate and hydrologic variables for the State of California and the watersheds that flow into it. These fine‐scaled climate data can be used in a variety of applications and analyses that may permit better research, modeling, and interpretation for resource management in the state. These variables were also developed to provide a standard set of down scaled climate of historic and baseline conditions, and future emissions scenarios for use by researchers in multiple sectors involved in the overall PIER V&A study. The idea was that even when future projections are uncertain, if the same projections are used by groups working in multiple sectors, then the results from each sector study may be more cross‐ comparable. We arrived at the grid‐scale and scenarios presented here through a series of steps that started with the identification of appropriate scenarios for California, based on Cayan et al. , and the use of fine‐scale down scaling for application to a regional hydrological model that can be evaluated on the basis of measured streamgage data. This paper documents the methodology used to develop 14 climatic and hydrologic variables at 270 meters for a 90‐year retrospective and a 90‐year forward projection, under two emissions scenarios and using two global climate models , as well as potential applications, accuracies, and uncertainties. It also describes the data preparation and distribution, and acknowledges the studies being conducted in parallel that have used the data for the V&A study and other ongoing studies. We provide detail on trends in the hydrologic variables, but not temperature, as this paper is primarily focused on hydrology. Much of climate change impact assessment and adaptation planning centers on water availability, for both human populations and ecological systems .
Projections of future climates from GCMs include the amount and timing of precipitation, as well as increases in air temperature, and are widely used in climate impact assessments . One of the needs in these assessments is a better understanding of what happens to precipitation in terrestrial ecosystems. The three main pathways—returning to the air via evaporation and plant transpiration; infiltration into soils and recharge to aquifers; and runoff—represent the water balance. Quantifying the relationship between these pathways can permit much more detailed predictions of the impacts of changing water availability to ecosystems and their inhabitants. Although climate change studies are fraught with uncertainty on the basis of emissions scenarios and GCMs used, the application of climate projections to mechanistic, process‐based, hydrologic modeling should not be cause to amplify the uncertainty in the GCM projections. In fact, the incorporation of deterministic processes and landscape characteristics can potentially be employed to reduce uncertainty in the projected hydrologic outcome. Validation of spatially explicit hydrologic models that quantify the water balance by comparing measured stream flow with model output is a promising approach to providing defensible mechanistic hydrologic relationships between climate and landscape in baseline time, that can then be applied to future climate projections for potentially more detailed forecasts. These will have increased utility over existing models for studies investigating climate impacts to species and ecosystems. Such a spatially vetted mechanistic model could then provide more robust projections of runoff,25 liter pot and thereby the other components of the water balance under future climates. Such capacity for these more detailed hydrologic predictions is critical for ecological studies and planning in the face of climate change.The search for operational scales of analysis to inform natural resources management drives a need for finer‐scale climate models. Global climate model outputs, typically range from 1.5–4.5 degrees , is too coarse for watershed‐specific assessments on all but the largest watersheds , requiring the need to convert this output to scales that appropriately reflect the environmental processes under consideration. Down scaling can bring climate projections to a spatial dimension for grid cells that can be validated using watershed‐based methods, applied to local landscapes, or analyzed across large regions. Depending on the process of concern, this down scaling may range from spatial extents of kilometers to meters. Down scaling was, therefore, the first step we took to develop projections of water‐balance components for California watersheds that are robust for use under climate change scenarios.
As projections maintain their own set of uncertainties on the basis of the assumption chosen for global climate modeling and greenhouse gas emissions scenarios, it is advisable to incur the least additional uncertainty attributable to the down scaling scheme itself.Many approaches to hydrologic modeling have been developed. The U.S. Geological Survey Precipitation‐Runoff Modeling System is being used to simulate flows under future climate conditions at the watershed scale . This approach requires daily temperature and precipitation values that are applied to individual watersheds and used in a deterministic, distributed‐parameter setting . The Variable Infiltration Capacity model is a spatially explicit physical hydrology model, generally run regionally at coarse spatial scales, that balances energy and water budgets and also runs using daily data . This model has also been applied to monthly climate in a model comparison study by Maurer et al. , who found that model selection was less important for capturing high flow timing but that for the low flows, the models they tested varied, implying a need to vet model performance, particularly for aridifying regions. These rainfall‐runoff models are specifically calibrated to streamgage data. Other hydrologic modeling approaches have used streamgage data to validate the model projections as well. Alkama et al. developed the Interactions between Soil, Biosphere, and Atmosphere‐Total Runoff Integrating Pathways and looked at multi‐decadalvariability in continental runoff from 1960–1994 using 154 large rivers with varying lengths of streamgage data for validation. Chiew et al. found that five different down scaling techniques all reproduced observed rainfall, and the runoff models used were capable of reproducing observed stream flows for eight basins in Australia. The range of applications and modeling platforms using stream flow for calibration indicates the utility of using the integrated measurement of stream flow in calibration exercises.All of these rainfall‐runoff models rely on soil storage in some capacity and do not incorporate bedrock properties; thus, they neglect the influence of bedrock permeability in estimates of recharge. There have been many experimental evaluations of hillslope processes and a few that have investigated the influence of bedrock permeability on hydrologic response to climate . Fewer still that have numerically modeled watersheds with the incorporation of bedrock properties . Generally, these models are two‐ or three‐ dimensional, finite‐element models that explicitly incorporate bedrock, but are computationally expensive and cover small areas. Historically, recharge estimates have relied on monthly water‐ balance models that incorporate simulations of evapotranspiration , inverse modeling , or lysimetry and tracer tests . Water‐balance modeling to assess both recharge and runoff has been done at the site scale and integrated with various measurements addressing different spatial scales . Watershed‐scale or regional‐scale modeling to estimate recharge and runoff has been done using water‐balance modeling by Hevesi et al. , Flint et al. , and Flint and Flint . Water‐balance models have been used to assess the impacts of climate change on hydrology, and in California the following water‐balance models have been previously used: VIC and CALSIM , the Precipitation‐Runoff Modeling System , Water Evaluation And Planning , and the Watershed Environmental Hydrology model , either at the watershed scale, or regionally. While many studies have evaluated impacts of climate change on ecological processes and the response of species to these changes , these evaluations are predominantly based on climate variables, without the integrating effects of hydrologic response. Indeed, most species‐distribution models rely solely on climatic variables and topography . Analyses of climate change impacts on ecosystems using climatic water deficit, with estimates of actual evapotranspiration, are beginning to emerge in the literature . However, the hydrologic results presented in this paper are provided at a fine spatial scale not yet seen applied in the literature that has the potential to further enhance the science and interpretation of climate change impacts on ecological systems.The Basin Characterization Model is a regional water balance model that has been applied to numerous watersheds in California at a fine scale of 270 m grid cells to assess impacts of climate change on both water availability and ecosystems. Using down scaled precipitation and air temperatures surfaces from 1971–2000, projections of runoff and recharge were produced for model calibration and assessment of model performance. This paper reports historic and future trends from the climatic input variables and from variables generated by the BCM: snow pack, potential evapotranspiration, actual evapotranspiration, and climatic water deficit .