Understanding the dynamics of solar energy systems by using simulation narratives

In this paper, we discuss the application of modern didactic approaches to solar energy education. We focus on the dynamics of decentralized energy systems and solar thermal applications. In order to bridge the gap between theory and practice, students are engaged in investigating solar systems in numerical analysis combined with hands-on laboratory exercises. Our learning material includes simulation software and state-of-the-art analysis tools for the post-processing of log data. We recognize similarities in the students’ cognitive processes when they do simulations in one part of their practical work and hardware experiments in the other part. In both cases, the narrative nature of the processes are a key to a fundamental understanding of the underlying physics. For both the simulation approach as well as the hardware experiments, students train to explain the physical processes in words: Simulation software and hardware laboratory equipment are the “story worlds” and a specific simulation run or a measurement experiment is the “story” (Fuchs 2015). Consequently, students at the same time practice clearly phrasing their observations and extend their expertise in solar energy. They also train abilities like system modeling, parameter validation, and practical skills like the handling of large data amounts typically produced by logging devices. We conclude that a narrative approach helps to thoroughly understand the controller strategies in solar systems with all its consequences and at the same time enables solar engineers for successful communication with the various players

Charge-Doping driven Evolution of Magnetism and non-Fermi-Liquid Behavior in the Filled Skutterudite CePt4Ge12-xSbx

The filled-skutterudite compound CePt4Ge12 is situated close to the border between intermediate-valence of Ce and heavy-fermion behavior. Substitution of Ge by Sb drives the system into a strongly correlated and ultimately upon further increasing the Sb concentration into an antiferromagnetically ordered state. Our experiments evidence a delicate interplay of emerging Kondo physics and the formation of a local 4f moment. An extended non-Fermi-liquid region, which can be understood in the framework of a Kondo-disorder model, is observed. Band-structure calculations support the conclusion that the physical properties are governed by the interplay of electron supply via Sb substitution and the concomitant volume effects.Comment: 5 pages, 3 Figur

Heat-capacity measurements under uniaxial pressure using a piezo-driven device

Y.S.L. acknowledges the support of a St Leonards scholarship from the University of St Andrews, the Engineering and Physical Sciences Research Council via the Scottish Condensed Matter Centre for Doctoral Training under Grant No. EP/G03673X/1, and the Max Planck Society.We report the development of a technique to measure heat capacity at large uniaxial pressure using a piezoelectric-driven device generating compressive and tensile strain in the sample. Our setup is optimized for temperatures ranging from 8 K down to millikelvin. Using an AC heat-capacity technique, we are able to achieve an extremely high resolution and to probe a homogeneously strained part of the sample. We demonstrate the capabilities of our setup on the unconventional superconductor Sr2RuO4. By replacing thermometer and adjusting the remaining setup accordingly, the temperature regime of the experiment can be adapted to other temperature ranges of interest.Publisher PDFPeer reviewe

Magnetism and unconventional superconductivity in Cen_nMm_mIn3n+2m_{3n+2m} heavy-fermion crystals

We review magnetic, superconducting and non-Fermi-liquid properties of the structurally layered heavy-fermion compounds Ce$_n$M$_m$In$_{3n+2m}$ (M=Co, Rh, Ir). These properties suggest d-wave superconductivity and proximity to an antiferromagetic quantum-critical point.Comment: submitted 23rd International Conference on Low Temperature Physics (LT-23), Aug. 200

The Bivariate Normal Copula

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.Comment: 24 page

Response of the Heavy-Fermion Superconductor CeCoIn5_5 to Pressure: Roles of Dimensionality and Proximity to a Quantum-Critical Point

We report measurements of the pressure-dependent superconducting transition temperature $T_c$ and electrical resistivity of the heavy-fermion compound CeCoIn$_5$. Pressure moves CeCoIn$_5$ away from its proximity to a quantum-critical point at atmospheric pressure. Experimental results are qualitatively consistent with theoretical predictions for strong-coupled, d-wave superconductivity in an anisotropic 3D superconductor.Comment: 9 pages, 5 figure

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Recon 2.2: from reconstruction to model of human metabolism.

IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001)

HopScotch - a low-power renewable energy base station network for rural broadband access

The provision of adequate broadband access to communities in sparsely populated rural areas has in the past been severely restricted. In this paper, we present a wireless broadband access test bed running in the Scottish Highlands and Islands which is based on a relay network of low-power base stations. Base stations are powered by a combination of renewable sources creating a low cost and scalable solution suitable for community ownership. The use of the 5~GHz bands allows the network to offer large data rates and the testing of ultra high frequency ``white space'' bands allow expansive coverage whilst reducing the number of base stations or required transmission power. We argue that the reliance on renewable power and the intelligent use of frequency bands makes this approach an economic green radio technology which can address the problem of rural broadband access

Environmental and Economically Conscious Magnesium Production: Solar Thermal Electrolytic Production of Mg from MgO

One method to improve the fuel efficiency of American made vehicles is to reduce vehicle weight by substituting steel components with lighter magnesium (Mg) components. Unfortunately, U.S. produced Mg currently costs approximately $3.31 per kg, over seven times the price of steel. Furthermore, Mg production has a staggering energy and environmental impact, consuming up to 102 kW-hr/kg-Mg of energy and producing 36 kg of CO2/kg-Mg. To reduce the overwhelming economic and environmental impact of Mg, a new solar thermal electrolytic process has been developed for the production of Mg from MgO. Through this process, liquid Mg is produced in a solar reactor utilizing both thermal and electrical energy. At elevated temperatures, the thermal energy from concentrated sunlight reduces the required electrical work below that of current processes. The reactor absorbs the concentrated solar energy, heating a molten salt-MgO mixture in an electrolytic cell. Electricity is then supplied to the cell, producing liquid Mg and CO. It is estimated that this new process will produce Mg at$2.50 per kg, with costs decreasing as the technology is further developed. This process requires approximately 8.3 kW-hr/kg-Mg of energy and produces only 3.44 kg of CO2/kg-Mg, large reductions compared to current processes