Calibrating whole building energy models: An evidence-based methodology

This paper reviews existing case studies and methods for calibrating whole building energy models to measured data. This research describes a systematic, evidence-based methodology for the calibration of these models. Under this methodology, parameter values in the final calibrated model reference the source of information used to make changes to the initial model. Thus, the final model is based solely on evidence. Version control software stores a complete record of the calibration process, and the evidence on which the final model is based. Future users can review the changes made throughout the calibration process along with the supporting evidence. In addition to the evidence-based methodology, this paper also describes a new zoning process that represents the real building more closely than the typical core and four perimeter zone approach. Though the methodology is intended to apply to detailed calibration studies with high resolution measured data, the primary aspects of the methodology (evidence-based approach, version control, and zone-typing) are independent of the available measured data.     

High yield polypyrrole: A novel approach to synthesis and characterization

An improved synthetic route to polypyrrole salt was accomplished using methanesulfonic acid as a novel dopant along with potassium persulfate as the oxidant employing inverted emulsion polymerization technique. Polypyrrole salt was obtained in high-weight percent yield (83.77%) with respect to the amount of monomer used and the reaction time was drastically reduced (1 h 10 min.) as compared to the previously reported synthesis methods. Characterization of the salt yielded satisfactory results. Inverted emulsion polymerization technique has several unique and distinct advantages over conventional techniques which facilitate the synthesis of fused five membered heterocyclic rings which are otherwise difficult to synthesize, and hence sparsely reported in the literature.     

Subsampling weakly dependent time series and application to extremes

This paper provides extensions of the work on subsampling by Bertail et al. in J. Econ. 120:295–326 (2004) for strongly mixing case to weakly dependent case by application of the results of Doukhan and Louhichi in Stoch. Proc. Appl. 84:313–342 (1999). We investigate properties of smooth and rough subsampling estimators for sampling distributions of converging and extreme statistics when the underlying time series is η- or λ-weakly dependent.     

Parabolic Flights @ Home

We developed an unmanned air vehicle (UAV) suitable for small parabolic-flight experiments. The flight speed of 100 m s^− 1 is sufficient for zero-gravity parabolas of 16 s duration. The flight path’s length of slightly more than 1 km and 400 m difference in altitude is suitable for ground controlled or supervised flights. Since this fits within the limits set for model aircraft, no additional clearance is required for operation. Our UAV provides a cost-effective platform readily available for low-g experiments, which can be performed locally without major preparation. A payload with a size of up to 0.9 ×0.3 ×0.3 m³ and a mass of ∼5 kg can be exposed to 0 g ₀–5 g ₀, with g ₀ being the gravitational acceleration of the Earth. Flight-duration depends on the desired acceleration level, e.g. 17 s at 0.17 g ₀ (lunar surface level) or 21 s at 0.38 g ₀ (Martian surface level). The aircraft has a mass of 25 kg (including payload) and a wingspan of 2 m. It is powered by a jet engine with an exhaust speed of 450 m s^− 1 providing a thrust of 180 N. The parabolic-flight curves are automated by exploiting the advantages of sophisticated micro-electronics to minimize acceleration errors.     

Studies on synthesis and microstructure evolution of multiphase in-situ composites based on Mo-Cr-Si system

This paper presents the results on in-situ synthesis of refractory metal-intermetallic composites (RMICs), Mo-16Cr-4Si and Mo-11Cr-9Si (wt.%) multiphase alloys and their characterization. The alloys were prepared from the oxides of molybdenum and chromium by their coreduction with Si as reductant. Exothermic nature of the synthesis reactions resulted in the formation of consolidated composite as a product in a single step. As-reduced alloys were remelted by arc melting and heat treatment was given. The evolution of phases and the microstructure were studied by XRD, SEM, and EDS analysis. The multiphase microstructure consist of the silicide phases (Mo,Cr)₃Si + (Mo,Cr)₅Si₃ for hypereutectic and (Mo,Cr)₃Si phase distributed in bcc matrix comprising essentially a solid solution of (Mo,Cr) for hypo-peritectic composition. Comparative studies of the synthesized alloys were also carried out to the composition, phases, microstructure, hardness and their oxidation behavior.     

A fast Monte Carlo algorithm for studying bottle-brush polymers

Obtaining reliable estimates of the statistical properties of complex macromolecules by computer simulation is a task that requires high computational effort as well as the development of highly efficient simulation algorithms. We present here an algorithm combining local moves, the pivot algorithm, and an adjustable simulation lattice box for simulating dilute systems of bottle-brush polymers with a flexible backbone and flexible side chains under good solvent conditions. Applying this algorithm to the bond fluctuation model, very precise estimates of the mean square end-to-end distances and gyration radii of the backbone and side chains are obtained, and the conformational properties of such a complex macromolecule are studied. Varying the backbone length (from Nb=67 to Nb=1027), side chain length (from N=0 to N=24 or 48), the scaling predictions for the backbone behavior as well as the side chain behavior are checked. We are also able to give a direct comparison of the structure factor between experimental data and the simulation results.     

Variational density matrix optimization using semidefinite programming

We discuss how semidefinite programming can be used to determine the second-order density matrix directly through a variational optimization. We show how the problem of characterizing a physical or N-representable density matrix leads to matrix-positivity constraints on the density matrix. We then formulate this in a standard semidefinite programming form, after which two interior point methods are discussed to solve the SDP. As an example we show the results of an application of the method on the isoelectronic series of Beryllium.