Comparison of software models for energy savings from cool roofs

A web-based Roof Savings Calculator (RSC) has been deployed for the United States Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. RSC simulates multiple roof and attic technologies for side-by-side comparison including reflective roofs, different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. Annual simulations of hour-by-hour, whole-building performance are used to provide estimated annual energy and cost savings from reduced HVAC use. While RSC reported similar cooling savings to other simulation engines, heating penalty varied significantly. RSC results show reduced cool roofing cost-effectiveness, thus mitigating expected economic incentives for this countermeasure to the urban heat island effect. This paper consolidates comparison of RSC's projected energy savings to other simulation engines including DOE-2.1E, AtticSim, Micropas, and EnergyPlus. Also included are comparisons to previous simulation-based studies, analysis of RSC cooling savings and heating penalties, the role of radiative heat exchange in an attic assembly, and changes made for increased accuracy of the duct model. Radiant heat transfer and duct interaction not previously modeled is considered a major contributor to heating penalties

Modeling singular mineralization processes due to fluid pressure fluctuations

Mineralization in the Earth's crust can be regarded as a singular process resulting in large amounts of mass accumulation and element enrichment over short time or space scales. The elemental concentrations modeled by fractals and multifractals show self-similarity and scale-invariant properties. We take the view that fluid-pressure variations in response to earthquakes or fault rupture are primarily responsible for changes in solubility and trigger transient physical and chemical variations in ore-forming fluids that enhance the mineralization process. Based on this general concept, we investigated mineral precipitation processes driven by rapid fluid pressure reductions by coupling mineralization to a cellular automaton model to reveal the nonlinear mechanism of the orogenic gold mineralization process using simulation. In the model, fluid pressure can increase to the rock failure condition, which was set as lithostatic pressure at a depth of 10 km (270 MPa), due to either porosity reduction or dehydration reactions. Rapid drops in pressure resulting from fault rupture or local hydrofracture may induce repeated gold precipitation. The geochemical patterns generated by the model evolve from depletion to enrichment patterns, and from spatially random to spatially clustered structures quantified by multifractal models and geostatistics. Results show how metal elements self-organize to form high metal concentration patterns displaying self-similarity and scale-invariance. These transitions are attributed to the growth and coalescence of sub-networks with different fluid pressures up to the percolation threshold, resulting in a wide range of fluid pressure reductions and gold precipitation in the form of clusters. The results suggest that cyclic evolution of fluid pressure and its effects on gold precipitation systems can effectively mimic the repeated mineralization superposition process, and generate complex geochemical patterns characterized by a multifractal model. The nonlinear behavior exhibits scale-invariance and self-organized critical threshold, where mineral phase separations result from fluid pressure reductions associated with fault failure

Equation modifying program, L219 (EQMOD). Volume 1: Engineering and usage

The analysis and use of the Equation Modifying Program (EQMOD) L219, digital computer program which modifies matrices according to specific instructions was described. The program modifies the theoretical equation of motion and load equations generated by the DYLOFLEX programs Equation of Motion L217 (EOM), and Load Equations, L218 (LOADS), respectively

Approximations of thermoelastic and viscoelastic control systems

Well-posed models and computational algorithms are developed and analyzed for control of a class of partial differential equations that describe the motions of thermo-viscoelastic structures. An abstract (state space) framework and a general well-posedness result are presented that can be applied to a large class of thermo-elastic and thermo-viscoelastic models. This state space framework is used in the development of a computational scheme to be used in the solution of a linear quadratic regulator (LQR) control problem. A detailed convergence proof is provided for the viscoelastic model and several numerical results are presented to illustrate the theory and to analyze problems for which the theory is incomplete

Magnetized Iron Atmospheres for Neutron Stars

Using a Hartree-Fock formalism, we estimate energy levels and photon cross sections for atomic iron in magnetic fields B ~ 10^13 G. Computing ionization equilibrium and normal mode opacities with these data, we construct LTE neutron star model atmospheres at 5.5 < Log(T_eff) < 6.5 and compute emergent spectra. We examine the dependence of the emergent spectra on T_eff and B. We also show the spectral variation with the angle between the magnetic field and the atmosphere normal and describe the significant limb darkening in the X-ray band. These results are compared with recent detailed computations of neutron star H model atmospheres in high fields and with low field Fe and H model atmospheres constructed from detailed opacities. The large spectral differences for different surface compositions may be discernible with present X-ray data; we also note improvements needed to allow comparison of Fe models with high quality spectra.Comment: 18 pages with 5 eps figures, accepted for publication in ApJ Replaced due to clerical error only: one more author, no new conten

Are eccentricity fluctuations able to explain the centrality dependence of v4v_4?

The fourth harmonic of the azimuthal distribution of particles $v_4$ has been measured for Au-Au collisions at the Relativistic Heavy Ion Collider (RHIC). The centrality dependence of $v_4$ does not agree with the prediction from hydrodynamics. In particular, the ratio $v_4/(v_2)^2$, where $v_2$ denotes the second harmonic of the azimuthal distribution of particles, is significantly larger than predicted by hydrodynamics. We argue that this discrepancy is mostly due to elliptic flow ($v_2$) fluctuations. We evaluate these fluctuations on the basis of a Monte Carlo Glauber calculation. The effect of deviations from local thermal equilibrium is also studied, but appears to be only a small correction. Combining these two effects allows us to reproduce experimental data for peripheral and midcentral collisions. However, we are unable to explain the large magnitude of $v_4/(v_2)^2$ observed for the most central collisions.Comment: talk presented at the Strangeness in Quark Matter Conference, Buzios, Brazil, Sept. 27 - oct. 2, 200

Looking back to see the future: building nuclear power plants in Europe

The so-called ‘nuclear renaissance’ in Europe is promulgated by the execution of two large engineering projects involving the construction of two European Pressurized Reactors (EPRs) in Flamanville, France and Olkiluoto in Finland. As both projects have faced budget overruns and delays, this paper analyses their governance and history to derive lessons useful for the construction of future projects. Analysis indicates that the reasons for these poor outcomes are: overoptimistic estimations, first-of-a-kind (FOAK) issues and undervaluation of regulation requirements. These pitfalls have the potential to impact on many other engineering construction projects and highlight fruitful areas of further research into project performance

Nasal lysine aspirin challenge in the diagnosis of aspirin - exacerbated respiratory disease

Background Aspirin-exacerbated respiratory disease is under-diagnosed and therefore effective and inexpensive therapy with aspirin desensitization is rarely performed. Methods We present an audit of 150 patients with difficult to treat nasal polyposis, 132 of whom also had asthma, 131 of whom underwent challenge with the only soluble form of aspirin, lysine aspirin (LAS), to confirm or exclude the diagnosis of aspirin-exacerbated respiratory disease (AERD). Results One hundred patients proved positive on nasal challenge, 31 who were negative went onto oral LAS challenge and a further 14 gave positive results, leaving 17 who were negative to a dose equivalent to over 375 mg of aspirin. Nineteen were not challenged because of contraindications. With the exception of one patient who developed facial angioedema and two patients with > 20% drop in FEV1 (following nasal plus oral challenge) no other severe adverse events occurred. No hospitalization was required for these three patients. Nasal inspiratory peak flow monitoring was less sensitive to obstruction caused by aspirin than was acoustic rhinometry – which should be employed when aspirin challenge is an outpatient procedure. Conclusions Provided patients are carefully chosen and monitored LAS challenge is suitable for ENT day case practice where respiratory physician help with asthma is available and should reduce the under-diagnosis of this condition

Denoising Autoencoders for fast Combinatorial Black Box Optimization

Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Autoencoders (AE) are generative stochastic networks with these desired properties. We integrate a special type of AE, the Denoising Autoencoder (DAE), into an EDA and evaluate the performance of DAE-EDA on several combinatorial optimization problems with a single objective. We asses the number of fitness evaluations as well as the required CPU times. We compare the results to the performance to the Bayesian Optimization Algorithm (BOA) and RBM-EDA, another EDA which is based on a generative neural network which has proven competitive with BOA. For the considered problem instances, DAE-EDA is considerably faster than BOA and RBM-EDA, sometimes by orders of magnitude. The number of fitness evaluations is higher than for BOA, but competitive with RBM-EDA. These results show that DAEs can be useful tools for problems with low but non-negligible fitness evaluation costs.Comment: corrected typos and small inconsistencie