Raytracing simulation for predicting light pipe transmittance

Daylighting systems can offer energy savings primarily by reducing electric lighting usage. Accurate predictive models of daylighting system performances are crucial for effective design and implementation of this renewable energy technology. A comparative study of predictive methods was performed and the use of a commercial raytracing software program was validated as a method of predicting light pipe performance. Raytracing simulation was shown to more accurately predict transmission effi ciency than existing analytical methods.

The unsteady flow of a weakly compressible fluid in a thin porous layer. I: Two-dimensional theory

We consider the problem of determining the pressure and velocity fields for a weakly compressible fluid flowing in a two-dimensional reservoir in an inhomogeneous, anisotropic porous medium, with vertical side walls and variable upper and lower boundaries, in the presence of vertical wells injecting or extracting fluid. Numerical solution of this problem may be expensive, particularly in the case that the depth scale of the layer h is small compared to the horizontal length scale l. This is a situation which occurs frequently in the application to oil reservoir recovery. Under the assumption that epsilon=h/l<<1, we show that the pressure field varies only in the horizontal direction away from the wells (the outer region). We construct two-term asymptotic expansions in epsilon in both the inner (near the wells) and outer regions and use the asymptotic matching principle to derive analytical expressions for all significant process quantities. This approach, via the method of matched asymptotic expansions, takes advantage of the small aspect ratio of the reservoir, epsilon, at precisely the stage where full numerical computations become stiff, and also reveals the detailed structure of the dynamics of the flow, both in the neighborhood of wells and away from wells.

Acclimation of photosynthesis to elevated CO2 in onion (Allium cepa) grown at a range of temperatures

Onion (Allium cepa) was grown in the field within temperature gradient tunnels (providing about -2.5degreesC to +2.5degreesC from outside temperatures) maintained at either 374 or 532 mumol mol(-1) CO2. Plant leaf area was determined non-destructively at 7 day intervals until the time of bulbing in 12 combinations of temperature and CO2 concentration. Gas exchange was measured in each plot at the time of bulbing, and the carbohydrate content of the leaf (source) and bulb (sink) was determined. Maximum rate of leaf area expansion increased with mean temperature. Leaf area duration and maximum rate of leaf area expansion were not significantly affected by CO2. The light-saturated rates of leaf photosynthesis (A(sat)) were greater in plants grown at normal than at elevated CO2 concentrations at the same measurement CO2 concentration. Acclimation of photosynthesis decreased with an increase in growth temperature, and with an increase in leaf nitrogen content at elevated CO2. The ratio of intercellular to atmospheric CO2 (C-i/C-a ratio) was 7.4% less for plants grown at elevated compared with normal CO2. A(sat) in plants grown at elevated CO2 was less than in plants grown at normal CO2 when compared at the same C-i Hence, acclimation of photosynthesis was due both to stomatal acclimation and to limitations to biochemical CO2 fixation. Carbohydrate content of the onion bulbs was greater at elevated than at normal CO2. In contrast, carbohydrate content was less at elevated compared with normal CO2 in the leaf sections in which CO2 exchange was measured at the same developmental stage. Therefore, acclimation of photosynthesis in fully expanded onion leaves was detected despite the absence of localised carbohydrate accumulation in these field-grown crops.

Acclimation of photosynthesis to elevated CO2 in onion (allium cepa) grown at a range of temperatures

Onion (Allium cepa) was grown in the field within temperature gradient tunnels (providing about -2.5 degrees C to +2.5 degrees C from outside temperatures) maintained at either 374 or 532 mumol mol (-1) CO2. Plant leaf area was determined non-destructively at 7 day intervals until the time of bulbing in 12 combinations of temperature and CO2 concentration. Gas exchange was measured in each plot at the time of bulbing, and the carbohydrate content of the leaf (source) and bulb (sink) was determined. Maximum rate of leaf area expansion increased with mean temperature. Leaf area duration and maximum rate of leaf area expansion were not significantly affected by CO2. The light-saturated rates of leaf photosynthesis (A(sat)) were greater in plants grown at normal than at elevated CO2 concentrations at the same measurement CO2 concentration. Acclimation of photosynthesis decreased with an increase in growth temperature, and with an increase in leaf nitrogen content at elevated CO2. The ratio of intercellular to atmospheric CO2 (C-i/C-a ratio) was 7.4% less for plants grown at elevated compared with normal CO2. A(sat) in plants grown at elevated CO2 was less than in plants grown at normal CO2 when compared at the same C-i Hence, acclimation of photosynthesis was due both to stomatal acclimation and to limitations to biochemical CO2 fixation. Carbohydrate content of the onion bulbs was greater at elevated than at normal CO2. In contrast, carbohydrate content was less at elevated compared with normal CO2 in the leaf sections in which CO2 exchange was measured at the same developmental stage. Therefore, acclimation of photosynthesis in fully expanded onion leaves was detected despite the absence of localised carbohydrate accumulation in these field-grown crops.

Reduced-order modeling of light transport in tissue for real-time monitoring of brain hemodynamics using diffuse optical tomography

This paper proposes a new reconstruction method for diffuse optical tomography using reduced-order models of light transport in tissue. The models, which directly map optical tissue parameters to optical flux measurements at the detector locations, are derived based on data generated by numerical simulation of a reference model. The reconstruction algorithm based on the reduced-order models is a few orders of magnitude faster than the one based on a finite element approximation on a fine mesh incorporating a priori anatomical information acquired by magnetic resonance imaging. We demonstrate the accuracy and speed of the approach using a phantom experiment and through numerical simulation of brain activation in a rat's head. The applicability of the approach for real-time monitoring of brain hemodynamics is demonstrated through a hypercapnic experiment. We show that our results agree with the expected physiological changes and with results of a similar experimental study. However, by using our approach, a three-dimensional tomographic reconstruction can be performed in ∼3  s per time point instead of the 1 to 2 h it takes when using the conventional finite element modeling approach

Multi-model assessment of stratospheric ozone return dates and ozone recovery in CCMVal-2 models

Projections of stratospheric ozone from a suite of chemistry-climate models (CCMs) have been analyzed. In addition to a reference simulation where anthropogenic halogenated ozone depleting substances (ODSs) and greenhouse gases (GHGs) vary with time, sensitivity simulations with either ODS or GHG concentrations fixed at 1960 levels were performed to disaggregate the drivers of projected ozone changes. These simulations were also used to assess the two distinct milestones of ozone returning to historical values (ozone return dates) and ozone no longer being influenced by ODSs (full ozone recovery). The date of ozone returning to historical values does not indicate complete recovery from ODSs in most cases, because GHG-induced changes accelerate or decelerate ozone changes in many regions. In the upper stratosphere where CO2-induced stratospheric cooling increases ozone, full ozone recovery is projected to not likely have occurred by 2100 even though ozone returns to its 1980 or even 1960 levels well before (~2025 and 2040, respectively). In contrast, in the tropical lower stratosphere ozone decreases continuously from 1960 to 2100 due to projected increases in tropical upwelling, while by around 2040 it is already very likely that full recovery from the effects of ODSs has occurred, although ODS concentrations are still elevated by this date. In the midlatitude lower stratosphere the evolution differs from that in the tropics, and rather than a steady decrease in ozone, first a decrease in ozone is simulated from 1960 to 2000, which is then followed by a steady increase through the 21st century. Ozone in the midlatitude lower stratosphere returns to 1980 levels by ~2045 in the Northern Hemisphere (NH) and by ~2055 in the Southern Hemisphere (SH), and full ozone recovery is likely reached by 2100 in both hemispheres. Overall, in all regions except the tropical lower stratosphere, full ozone recovery from ODSs occurs significantly later than the return of total column ozone to its 1980 level. The latest return of total column ozone is projected to occur over Antarctica (~2045–2060) whereas it is not likely that full ozone recovery is reached by the end of the 21st century in this region. Arctic total column ozone is projected to return to 1980 levels well before polar stratospheric halogen loading does so (~2025–2030 for total column ozone, cf. 2050–2070 for Cly+60×Bry) and it is likely that full recovery of total column ozone from the effects of ODSs has occurred by ~2035. In contrast to the Antarctic, by 2100 Arctic total column ozone is projected to be above 1960 levels, but not in the fixed GHG simulation, indicating that climate change plays a significant role.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

First structural analysis of a naphthalene-based poly(ether ketone): Crystal and molecular simulation from X-ray powder data and diffraction modeling

Polycondensation of 2,6-dihydroxynaphthalene with 4,4'-bis(4"-fluorobenzoyl)biphenyl affords a novel, semicrystalline poly(ether ketone) with a melting point of 406 degreesC and glass transition temperature (onset) of 168 degreesC. Molecular modeling and diffraction-simulation studies of this polymer, coupled with data from the single-crystal structure of an oligomer model, have enabled the crystal and molecular structure of the polymer to be determined from X-ray powder data. This structure-the first for any naphthalene-containing poly(ether ketone)-is fully ordered, in monoclinic space group P2(1)/b, with two chains per unit cell. Rietveld refinement against the experimental powder data gave a final agreement factor (R-wp) of 6.7%.

Last Glacial Maximum CO2 and δ13C successfully reconciled

During the Last Glacial Maximum (LGM, ∼21,000 years ago) the cold climate was strongly tied to low atmospheric CO2 concentration (∼190 ppm). Although it is generally assumed that this low CO2 was due to an expansion of the oceanic carbon reservoir, simulating the glacial level has remained a challenge especially with the additional δ13C constraint. Indeed the LGM carbon cycle was also characterized by a modern-like δ13C in the atmosphere and a higher surface to deep Atlantic δ13C gradient indicating probable changes in the thermohaline circulation. Here we show with a model of intermediate complexity, that adding three oceanic mechanisms: brine induced stratification, stratification-dependant diffusion and iron fertilization to the standard glacial simulation (which includes sea level drop, temperature change, carbonate compensation and terrestrial carbon release) decreases CO2 down to the glacial value of ∼190 ppm and simultaneously matches glacial atmospheric and oceanic δ13C inferred from proxy data. LGM CO2 and δ13C can at last be successfully reconciled.

Influence of probabilistic climate projections on building energy simulation

The Chartered Institute of Building Service Engineers (CIBSE) produced a technical memorandum (TM36) presenting research on future climate impacting building energy use and thermal comfort. One climate projection for each of four CO2 emissions scenario were used in TM36, so providing a deterministic outlook. As part of the UK Climate Impacts Programme (UKCIP) probabilistic climate projections are being studied in relation to building energy simulation techniques. Including uncertainty in climate projections is considered an important advance to climate impacts modelling and is included in the latest UKCIP data (UKCP09). Incorporating the stochastic nature of these new climate projections in building energy modelling requires a significant increase in data handling and careful statistical interpretation of the results to provide meaningful conclusions. This paper compares the results from building energy simulations when applying deterministic and probabilistic climate data. This is based on two case study buildings: (i) a mixed-mode office building with exposed thermal mass and (ii) a mechanically ventilated, light-weight office building. Building (i) represents an energy efficient building design that provides passive and active measures to maintain thermal comfort. Building (ii) relies entirely on mechanical means for heating and cooling, with its light-weight construction raising concern over increased cooling loads in a warmer climate. Devising an effective probabilistic approach highlighted greater uncertainty in predicting building performance, depending on the type of building modelled and the performance factors under consideration. Results indicate that the range of calculated quantities depends not only on the building type but is strongly dependent on the performance parameters that are of interest. Uncertainty is likely to be particularly marked with regard to thermal comfort in naturally ventilated buildings.

Multi-agent based modeling and simulation of complex system in hospital

This study puts forward a method to model and simulate the complex system of hospital on the basis of multi-agent technology. The formation of the agents of hospitals with intelligent and coordinative characteristics was designed, the message object was defined, and the model operating mechanism of autonomous activities and coordination mechanism was also designed. In addition, the Ontology library and Norm library etc. were introduced using semiotic method and theory, to enlarge the method of system modelling. Swarm was used to develop the multi-agent based simulation system, which is favorable for making guidelines for hospital's improving it's organization and management, optimizing the working procedure, improving the quality of medical care as well as reducing medical charge costs.