Eddy current damper

A high torque capacity eddy current damper used as a rate limiting device for a large solar array deployment mechanism is discussed. The eddy current damper eliminates the problems associated with the outgassing or leaking of damping fluids. It also provides performance advantages such as damping torque rates, which are truly linear with respect to input speed, continuous 360 degree operation in both directions of rotation, wide operating temperature range, and the capability of convenient adjustment of damping rates by the user without disassembly or special tools

Supersymmetric Dark Matter - How Light Can the LSP Be?

Using a very minimal set of theoretical assumptions we derive a lower limit on the LSP mass in the MSSM. We only require that the LSP be the lightest neutralino, that it be responsible for the observed relic density and that the MSSM spectrum respect the LEP2 limits. We explicitly do not require any further knowledge about the MSSM spectrum or the mechanism of supersymmetry breaking. Under these assumptions we determine a firm lower limit on the neutralino LSP mass of 18\gev. We estimate the effect of improved limits on the cold dark matter relic density as well as the effects of improved LEP2-type limits from a first stage of TESLA on the allowed range of neutralino LSP masses.Comment: 12 pages, 3 Figures, v2: published versio

Cover crops in Missouri : putting them to work on your farm (2016)

New 8/15; Link updates 4/16/Web

Using data assimilation to optimize pedotransfer functions using field-scale in situ soil moisture observations

Soil moisture predictions from land surface models are important in hydrological, ecological, and meteorological applications. In recent years, the availability of wide-area soil moisture measurements has increased, but few studies have combined model-based soil moisture predictions with in situ observations beyond the point scale. Here we show that we can markedly improve soil moisture estimates from the Joint UK Land Environment Simulator (JULES) land surface model using field-scale observations and data assimilation techniques. Rather than directly updating soil moisture estimates towards observed values, we optimize constants in the underlying pedotransfer functions, which relate soil texture to JULES soil physics parameters. In this way, we generate a single set of newly calibrated pedotransfer functions based on observations from a number of UK sites with different soil textures. We demonstrate that calibrating a pedotransfer function in this way improves the soil moisture predictions of a land surface model at 16 UK sites, leading to the potential for better flood, drought, and climate projections

The Faint End Slopes Of Galaxy Luminosity Functions In The COSMOS 2-Square Degree Field

We examine the faint-end slope of the rest-frame V-band luminosity function (LF), with respect to galaxy spectral type, of field galaxies with redshift z<0.5, using a sample of 80,820 galaxies with photometric redshifts in the Cosmic Evolution Survey (COSMOS) field. For all galaxy spectral types combined, the LF slope, alpha, ranges from -1.24 to -1.12, from the lowest redshift bin to the highest. In the lowest redshift bin (0.02<z<0.1), where the magnitude limit is M(V) ~ -13, the slope ranges from ~ -1.1 for galaxies with early-type spectral energy distributions (SEDs), to ~ -1.9 for galaxies with low-extinction starburst SEDs. In each galaxy SED category (Ell, Sbc, Scd/Irr, and starburst), the faint-end slopes grow shallower with increasing redshift; in the highest redshift bin (0.4<z<0.5), the slope is ~ -0.5 and ~ -1.3 for early-types and starbursts respectively. The steepness of alpha at lower redshift could be qualitatively explained by large numbers of faint dwarf galaxies, perhaps of low surface brightness, which are not detected at higher redshifts.Comment: 24 pages including 5 figures, accepted to ApJ

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Comparison of Met Office regional model soil moisture with COSMOS‐UK field‐scale in situ observations

The UK Met Office state-of-the-art, deterministic, convection-permitting, coupled land-atmosphere, regional weather forecasting system, known as the UKV or UK Variable resolution model (Tang et al. Meteorological Applications, 2013; 20:417–426), has been operational since 2015. Science updates are regularly made to the UKV land surface data assimilation scheme when those updates improve predictions of screen temperature and humidity, since these quantities have a direct impact on atmospheric states and weather forecasts. Less attention has been paid to whether UKV soil moisture analyses are close to independent, in-situ soil moisture observations, partly because it is difficult to make meaningful comparisons between 1.5 km2 gridded model outputs and traditional point sensor measurements. Soil moisture is recognized to be important when hydrological forecasts for runoff and rivers are required. This is because soil moisture controls the extent to which rainfall can infiltrate the soil, and the amount of surface runoff affects the timing of peak river flows (Ward & Robinson, Principles of Hydrology. McGraw-Hill Publishing Company; 2000; Singh et al. Water Resources Research, 2021, 57, e2020WR028827). Gómez et al. (Remote Sensing, 2020; 12:3691) report benefits to river flow forecasts when using soil moisture data assimilation in the UKV system instead of a daily downscaled product from the Met Office global model. The Met Office measures soil temperature and soil moisture at Cardington (Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279–295); there is no other UK Met Office site at which soil moisture is measured. In this study, we use field-scale (~200 m radius) soil moisture measurements from the UK Centre for Ecology and Hydrology's (UKCEH's) COSMOS-UK network to provide independent verification and analysis of UKV soil moisture during summer 2018, an unusually dry period in the United Kingdom. We find that the match to COSMOS-UK soil moisture observations is generally good, and that changes made to the land data assimilation approach during a recent operational upgrade had a generally beneficial impact on UKV soil moisture analyses under very dry conditions

A clustering approach to reduce computational expense in land surface models: a case study using JULES vn5.9

Land surface models such as JULES (the Joint UK Land Environment Simulator) are usually run on a regular, rectilinear grid, resulting in gridded outputs for variables such as soil moisture and water fluxes. Here we investigate a method of clustering grid cells with similar characteristics together in JULES. Clustering grid cells has the potential to reduce computational expense as well as providing an alternative to tiling approaches for capturing sub-grid heterogeneity. In this study, we cluster grid cells exclusively in the land surface part of modelling, i.e., separate from river routing. We compare gridded and clustered soil moisture outputs from JULES with measurements from the UK Centre for Ecology and Hydrology (UKCEH) COSMOS-UK network and show that the clustering approach can model soil moisture well while reducing computational expense. However, soil moisture results are dependent on the characteristics used to create the clusters. We investigate the effect of using clusters on predicted river flows, and compare routed JULES outputs with NRFA gauge data in the catchment. We show that less expensive JULES clustered outputs give similar river flow results to standard gridded outputs when routed at the grid resolution, and are able to match observed river flow better than gridded outputs when routed at higher resolution