Merging of the alpha and beta relaxations and aging via the Johari–Goldstein modes in rapidly quenched metallic glasses

This paper provides evidence that the physical aging of deeply and rapidly quenched metallic glasses is promoted by the Johari–Goldstein slow beta relaxation, resulting in a significant irreversible increase in the mechanical modulus on initial heating. Dynamic mechanical analysis has been used to characterize relaxation phenomena of a strong and a fragile metallic glass. In addition, we can extrapolate the temperature dependence of beta- and alpha-relaxation peaks to higher temperatures and calculate the merging temperature for both types of glasses

Large Scale Deployment of PV Units in Existing Distribution Networks: Optimization of the Installation Layout

In fixed PV installations, the azimuth and tilt of the panels are normally chosen with the objective of maximizing the plant capacity factor. In this paper, we show that when considering distribution networks with densely clustered PV plants, there exist installation criteria other than the conventional that achieves larger amount of PV generated electricity without violating distribution network constraints. In particular, we formulate an optimization problem to determine the siting, sizing, azimuth and tilt of the panels in order to maximize the PV production over a year while respecting the power grid voltage and line ampacity constraints. As a case study, we consider a Swiss distribution network and synthetic irradiance data for the considered area using a clear-sky model. We use the case study to compare the conventional way of installing PV panels vs the proposed method and show that the latter can nearly achieve a 6% increase in the generated PV electricity

Using GIS data and satellite-derived irradiance to optimize siting of PV installations in Switzerland

For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland

Optimized market value of alpine solar photovoltaic installations

Solar photovoltaic (PV) is the most rapidly expanding renewable resource worldwide. Yet, its full potential may be hindered by mismatches with market demand and correlated production profiles. In this research, we explore a case study of innovative PV placements in alpine regions using two, soft-linked optimization models of Switzerland's electricity system. Using Swissmod, an electricity dispatch and load-flow model, and OREES, an electricity system model employing evolution strategy to optimize PV placement, we simulate market prices of optimized PV placements given multiple years of weather data, various CO2 prices, and considering future electricity infrastructure developments across Europe. Mountain placements result in higher market value and less required area relative to lower-altitude PV placement strategies. The higher market value is driven by better alignment with demand, particularly during winter when demand is highest. We found that optimized alpine placements offer revenues of panel capacity (EUR/kW/year) that are on average 20% higher than revenues from urban PV installations. Furthermore, the Swiss mountains could host more than 1 GW of capacity with even greater revenues (33%). Alpine PV installations, with their higher market values and increased value factors, can potentially be very profitable investments and are also valuable from a system perspective

Reconstruction of heterogeneous snow water equivalent from MODIS imagery and energy balance modeling

Snow water equivalent (SWE) and its heterogeneity are two essential variables in the hydrologic cycle of a mountain environment. The first chapter explores two different modeling approaches to quantify a basin's snow pack: (1) forward modeling with the snow energy balance model Isnobal, and (2) reconstruction based on potential melt from Isnobal combined with fractional snow covered area from MODIS imagery, carried on the Terra and Aqua satellites. Basin-wide SWE and its heterogeneity were modelled for four water years in the Marble Fork of the Kaweah River, a 152 km2 basin in the Sierra Nevada. Two components of the heterogeneity of SWE were examined: that owing to accumulation and that resulting from snowmelt. Heterogeneity caused by accumulation is represented by reconstructed SWE before the onset of melt. It is highest above the timberline, where wind causes redistribution and sublimation. Reconstruction accounts for the heterogeneity of wind-redistributed snow at the beginning of the melt season, even though it does not model the actual distribution processes. Thus it provides an independent method of measuring the spatial distribution of snow, which is useful to validate models of snow accumulation, either owing to redistribution or to precipitation itself. Heterogeneity caused by melt emerges from the calculations in Isnobal. Throughout spring it stays low above the timberline, while an increase occurs at the lowest snow-covered elevations as well as at the transition between forested and open areas. The spatial distribution of these trends persists in all four years of the study, but in the wettest year, 2006, the delayed onset of melt muted the heterogeneity. Forest cover is the dominating factor, with intermediate canopy cover causing the highest heterogeneity in melt. As input to the reconstruction model, fractional snow covered area from MODIS (fSCA) is corrected for missing data, periodic fluctuations caused by the satellite orbit, clouds, and vegetation cover. These uncertainties propagate into the reconstruction, and their effects on modeled SWE are treated in chapter 2. Two potential uncertainties are analyzed: a bias in fSCA that scales with vegetation cover and an offset in final melt-out date. While a positive bias in fSCA has little effect, a negative bias alters reconstructed SWE. Prolonging the melt season increases SWE more than shortening decreases it (4%-12% increase per day versus 3%-6% decrease per day). Chapter 3 presents an analysis of the spatial distribution of precipitation in the densely monitored Reynolds Creek Experimental watershed in Southwest Idaho. Elevation-detrended kriging yields interpolation surfaces similar to the PRISM precipitation model but is able to capture local anomalies such as rain shadow and topographic exposure. A comparison between summed hourly and daily precipitation surfaces illustrates the importance of interpolating precipitation at high temporal resolution in regions spanning the rain-snow transition. Otherwise, errors in the partitioning between rain and snow contaminate the daily interpolation results, when the elevation of phase transition varied frequently

Topographic distribution of snow water equivalent in the Sierra Nevada

Water supply forecasts in the Sierra Nevada using ground-based measurements of snow water equivalent (SWE) are uncertain because neither point measurements nor transects adequately explain spatial or temporal vari- ability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover in 2006 with energy balance calculations to reconstruct the SWE values throughout the melt season. Model estimates when compared to snow pillows at maximum accumulation are unbiased and have an RMS error of 297 to 417 mm. We compare this retrospective calculation of distributed SWE with two real-time models: (i) interpola- tion from pillows, courses, and satellite snow cover, and (ii) the Snow Data Assimilation System (SNODAS). The interpolation and SNODAS models show complete melt out more than a month earlier than reconstruction, and their total SWE volumes are 68% and 87% of the reconstructed volume. At elevations below 1500 m, the recon- struction model has less total SWE because of early season melt. Above 3000 m, the reconstruction shows more SWE than the real time models, which depend on surface measurements that do not sample the higher elevations. The results indicate that spatial patterns from the reconstruction could improve estimates of snow accumulation and duration.Funded by Naval Postgraduate School.NASACooperative Agreement NNG04GC52A (NASA)Award N00244-07-1-0013 (NPS)Earth Systems Science Fellowship program (NASA