Jason Brown

Quantitative analysis of tethered and free-swimming copepodid flow fields

SUMMARY We quantified the flow field generated by tethered and free-swimming Euchaeta antarctica using the particle image velocimetry (PIV) technique. The streamlines around the free-swimming specimens were generally parallel to the body axis, whereas the streamlines around all of the tethered copepodids demonstrated increased curvature. Differences noted in the streamline pattern, and hence the vorticity, dissipation rate and strain rate fields, are explained by considering the forces on the free-swimming specimen compared to the tethered specimen. Viscous flow theory demonstrates that the force on the fluid due to the presence of the tether irrevocably modifies the flow field in a manner that is consistent with the measurements. Hence, analysis of the flow field and all associated calculations differ for tethered versus free-swimming conditions. Consideration of the flow field of the free-swimming predatory copepodid shows the intensity of the biologically generated flow and the extent of the mechanoreceptive signal quantified in terms of shear strain rate. The area in the dorso-ventral view surrounded by the 0.5 s-1 contour of exy, which is a likely threshold to induce an escape response, is 11 times the area of the exoskeletal form for the free-swimming case. Thus, mechanoreceptive predators will perceive a more spatially extended signal than the body size.

Mitochondrial metabolic suppression and reactive oxygen species production in liver and skeletal muscle of hibernating thirteen-lined ground squirrels

During hibernation, animals cycle between periods of torpor, during which body temperature (T(b)) and metabolic rate (MR) are suppressed for days, and interbout euthermia (IBE), during which T(b) and MR return to resting levels for several hours. In this study, we measured respiration rates, membrane potentials, and reactive oxygen species (ROS) production of liver and skeletal muscle mitochondria isolated from ground squirrels (Ictidomys tridecemlineatus) during torpor and IBE to determine how mitochondrial metabolism is suppressed during torpor and how this suppression affects oxidative stress. In liver and skeletal muscle, state 3 respiration measured at 37°C with succinate was 70% and 30% lower, respectively, during torpor. In liver, this suppression was achieved largely via inhibition of substrate oxidation, likely at succinate dehydrogenase. In both tissues, respiration by torpid mitochondria further declined up to 88% when mitochondria were cooled to 10°C, close to torpid T(b). In liver, this passive thermal effect on respiration rate reflected reduced activity of all components of oxidative phosphorylation (substrate oxidation, phosphorylation, and proton leak). With glutamate + malate and succinate, mitochondrial free radical leak (FRL; proportion of electrons leading to ROS production) was higher in torpor than IBE, but only in liver. With succinate, higher FRL likely resulted from increased reduction state of complex III during torpor. With glutamate + malate, higher FRL resulted from active suppression of complex I ROS production during IBE, which may limit ROS production during arousal. In both tissues, ROS production and FRL declined with temperature, suggesting ROS production is also reduced during torpor by passive thermal effects.

Effects of dietary polyunsaturated fatty acids on mitochondrial metabolism in mammalian hibernation.

SUMMARY Thirteen-lined ground squirrels (Spermophilus tridecemlineatus) were fed one of four isocaloric, isolipemic diets containing 16, 22, 35 or 55 mg linoleic acid (18:2n-6) per gram. Mitochondrial properties were compared between hibernating and summer active states, and between diet groups. As in other studies, state 3 respiration was significantly reduced in hibernation, but only in animals fed the 22 mg g–1 18:2 diet. In the other diet groups, there was no difference in state 3 respiration between the hibernating and summer active groups. In the 22 mg g–1 18:2 diet group, there was no difference in mitochondrial proton conductance between hibernating and summer active animals, again in agreement with earlier studies. However, for all other diet groups, mitochondrial proton conductance was significantly reduced during hibernation. Mitochondrial phospholipid fatty acids changed significantly with hibernation, including increases in unsaturation indices and n-6/n-3, but no differences were found among diet groups. Mitochondrial proton conductance in hibernation showed a positive correlation with the content of linoleic acid (18:2) and arachidonic acid (20:4) in mitochondrial phospholipids. Lipid peroxidation was higher in mitochondria from hibernating animals, probably due to higher unsaturation, but there was no effect of dietary 18:2 on this pattern. Despite the dietary effects on mitochondrial metabolism, all animals hibernated with no differences in bout durations, body temperatures or whole-animal metabolic rates among the diet groups. The reduced mitochondrial proton leak in the 15, 35 and 55 mg g–1 18:2 diet groups might compensate for the inability to suppress respiration, permitting whole-animal energy savings over the hibernation season.

Analysis of the flow field of the krill, Euphausia pacifica

Velocity measurements were performed for the flow field generated by tethered krill Euphausia pacifica. The particle image velocimetry (PIV) technique was used to measure the velocity field in vertical planes aligned with the krill body axis. The krill generates a narrow jet-like flow behind and below the pleopods (roughly 25° below horizontal). The volume of fluid moving at greater than 10% of the maximum velocity near the pleopods is roughly 18 times larger than the volume of the krill. Thus, the hydrodynamic disturbance occupies a significantly larger region than the animal body. Other krill, sensing the flow disturbance, may take advantage of the flow induced by a neighbor to locate a mate or to draft for efficient propulsion.

Urban Data and Building Energy Modeling: A GIS-Based Urban Building Energy Modeling System Using the Urban-EPC Engine

There is a lack of building energy modeling in current planning support systems (PSS) while building energy efficiency is getting greater attention. This is due to the current limitations of energy modeling at the urban scale and the inconsistency between the available urban data and that required for modeling. The chapter seeks to fill this gap by developing a GIS-based urban building energy modeling system, using the Urban-EPC simulation engine, a modified Energy Performance Calculator engine. This modeling system is compatible with other planning tools, enhanced by the combination of physical and statistical modeling, and adjustable in its resolution, speed and accuracy. Through processing the Data Preparation, Pre-Simulation, Main Simulation and Visualization and Analysis models in this energy modeling system, the urban data related to the basic building information, mutual shading, microclimate and occupant behavior are collected, modified, and synthesized in the GIS platform and then used as the input of the Urban-EPC engine to get energy use of every building in a city, which could be further visualized and analyzed. The method is applied in Manhattan to show its potential as an important component in PSS to inform urban energy policy making.

Assessment of uncertainty and confidence in building design exploration

Abstract Performance assessment at early stages of buildings design is complicated by an inherent lack of information on the design and the uncertainty in how a building design may evolve to a final design. This pilot study reports on an initial quantification of such uncertainty associated with building energy performance and develops a method for informing decision makers of the risks in early design decisions under this uncertainty. Two case studies of building design decision situations under this uncertainty are explored along with using two different energy modeling tools: a reduced-order model and a high-order model. The intended contribution is to identify if a decision can be made with confidence in early design given a high level of uncertainty in the evolution of a design and what models can support decisions of this sort. Integration of the proposed decision support approach with a computer-aided design model is shown as well.

Building Energy Performance Estimation in Early Design Decisions: Quantification of Uncertainty and Assessment of Confidence

Building energy assessment models support design decisions, which should only be made if stakeholders are confident that the decision taken will result in a preferred outcome. Despite this fundamental notion, the assessment of confidence in decisions is not included in current energy assessment tools. Uncertainties in model inputs and in the appropriateness of the models used leads to uncertainty in model outputs and therefore to a reduction of confidence in the decisions supported by those outputs. In early design stages there is great uncertainty about how a design might evolve, which leads to large uncertainties in predicted outcomes, rendering the appropriateness of performance prediction to the decision questionable at this phase unless these uncertainties are quantified and used in performance predictions. Here we propose a quantification of these uncertainties and preliminarily examine their impact on confidence in design decisions using a case study.

A new approach to performance-based building design exploration using linear inverse modeling

Despite the development of a large number of building performance simulation tools, designers still need a systematic framework appropriate for energy-oriented decision-making in the early stages of design. While the current workflow follows a “forward” modelling procedure in which simulation tools predict the performance of a design, this study proposes an “inverse” procedure that entails a performance objective that estimates design parameters. Using linear inverse modelling, this approach generates plausible ranges for design parameters given a preferred thermal performance. The paper begins by demonstrating that thermal demand in a particular building operation-and-climate condition can be expressed as a linear regression model and then, in two case-studies, uses the regression model to develop an inverse algorithm. After defining energy performance targets as input, users obtain a probabilistic estimate of design parameters as output that represents a large “menu” of feasible design solutions, provides confidence, and embodies the iterative nature of design.