A hierarchy for modeling high speed propulsion systems

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery, such as inlets, ramjets, and scramjets. The discussion is separated into four areas: (1) computational fluid dynamics models for the entire nonlinear system or high order nonlinear models; (2) high order linearized models derived from fundamental physics; (3) low order linear models obtained from the other high order models; and (4) low order nonlinear models (order here refers to the number of dynamic states). Included in the discussion are any special considerations based on the relevant control system designs. The methods discussed are for the quasi-one-dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, including moving normal shocks, hammershocks, simple subsonic combustion via heat addition, temperature dependent gases, detonations, and thermal choking. The report also contains a comprehensive list of papers and theses generated by this grant

A simple method for simulating gasdynamic systems

A simple method for performing digital simulation of gasdynamic systems is presented. The approach is somewhat intuitive, and requires some knowledge of the physics of the problem as well as an understanding of the finite difference theory. The method is explicitly shown in appendix A which is taken from the book by P.J. Roache, 'Computational Fluid Dynamics,' Hermosa Publishers, 1982. The resulting method is relatively fast while it sacrifices some accuracy

Temperature control in continuous furnace by structural diagram method

The fundamentals of the structural diagram method for distributed parameter systems (DPSs) are presented and reviewed. An example is given to illustrate the application of this method for control design

Approximate truncated balanced realizations for infinite dimensional systems

This paper presents an approximate method for obtaining truncated balance realizations of systems represented by non-rational transfer functions, that is infinite dimensional systems. It is based on the approximation to the Hankel operator

Physical lumping methods for developing linear reduced models for high speed propulsion systems

In gasdynamic systems, information travels in one direction for supersonic flow and in both directions for subsonic flow. A shock occurs at the transition from supersonic to subsonic flow. Thus, to simulate these systems, any simulation method implemented for the quasi-one-dimensional Euler equations must have the ability to capture the shock. In this paper, a technique combining both backward and central differencing is presented. The equations are subsequently linearized about an operating point and formulated into a linear state space model. After proper implementation of the boundary conditions, the model order is reduced from 123 to less than 10 using the Schur method of balancing. Simulations comparing frequency and step response of the reduced order model and the original system models are presented

Anterior Hippocampus and Goal-Directed Spatial Decision Making

Contains fulltext : 115487.pdf (publisher's version ) (Open Access

A data driven approach to understanding the organization of high-level visual cortex

The neural representation in scene-selective regions of human visual cortex, such as the PPA, has been linked to the semantic and categorical properties of the images. However, the extent to which patterns of neural response in these regions reflect more fundamental organizing principles is not yet clear. Existing studies generally employ stimulus conditions chosen by the experimenter, potentially obscuring the contribution of more basic stimulus dimensions. To address this issue, we used a data-driven approach to describe a large database of scenes (>100,000 images) in terms of their visual properties (orientation, spatial frequency, spatial location). K-means clustering was then used to select images from distinct regions of this feature space. Images in each cluster did not correspond to typical scene categories. Nevertheless, they elicited distinct patterns of neural response in the PPA. Moreover, the similarity of the neural response to different clusters in the PPA could be predicted by the similarity in their image properties. Interestingly, the neural response in the PPA was also predicted by perceptual responses to the scenes, but not by their semantic properties. These findings provide an image-based explanation for the emergence of higher-level representations in scene-selective regions of the human brain

Temporal precision and the capacity of auditory-verbal short-term memory

The capacity of serially-ordered auditory-verbal short-term memory (AVSTM) is sensitive to the timing of the material to be stored, and both temporal processing and AVSTM capacity are implicated in the development of language. We developed a novel “rehearsal-probe” task to investigate the relationship between temporal precision and the capacity to remember serial order. Participants listened to a sub-span sequence of spoken digits and silently rehearsed the items and their timing during an unfilled retention interval. After an unpredictable delay, a tone prompted report of the item being rehearsed at that moment. An initial experiment showed cyclic distributions of item responses over time, with peaks preserving serial order and broad, overlapping tails. The spread of the response distributions increased with additional memory load and correlated negatively with participants’ auditory digit spans. A second study replicated the negative correlation and demonstrated its specificity to AVSTM by controlling for differences in visuo-spatial STM and nonverbal IQ. The results are consistent with the idea that a common resource underpins both the temporal precision and capacity of AVSTM. The rehearsal-probe task may provide a valuable tool for investigating links between temporal processing and AVSTM capacity in the context of speech and language abilities

Patterns of neural response in scene-selective regions of the human brain are affected by low-level manipulations of spatial frequency

Neuroimaging studies have found distinct patterns of response to different categories of scenes. However, the relative importance of low-level image properties in generating these response patterns is not fully understood. To address this issue, we directly manipulated the low level properties of scenes in a way that preserved the ability to perceive the category. We then measured the effect of these manipulations on category-selective patterns of fMRI response in the PPA, RSC and OPA. In Experiment 1, a horizontal-pass or vertical-pass orientation filter was applied to images of indoor and natural scenes. The image filter did not have a large effect on the patterns of response. For example, vertical- and horizontal-pass filtered indoor images generated similar patterns of response. Similarly, vertical- and horizontal-pass filtered natural scenes generated similar patterns of response. In Experiment 2, low-pass or high-pass spatial frequency filters were applied to the images. We found that image filter had a marked effect on the patterns of response in scene-selective regions. For example, low-pass indoor images generated similar patterns of response to low-pass natural images. The effect of filter varied across different scene-selective regions, suggesting differences in the way that scenes are represented in these regions. These results indicate that patterns of response in scene-selective regions are sensitive to the low-level properties of the image, particularly the spatial frequency content

The Behavioural Inhibition System, anxiety and hippocampal volume in a non-clinical population

Background: Animal studies have suggested that the hippocampus may play an important role in anxiety as part of the Behavioural Inhibition System (BIS), which mediates reactivity to threat and punishment and can predict an individual’s response to anxiety-relevant cues in a given environment. The aim of the present structural magnetic resonance imaging (MRI) study was to examine the relationship between individual differences in BIS and hippocampal structure, since this has not received sufficient attention in non-clinical populations. Thirty healthy right-handed participants with no history of alcohol or drug abuse, neurological or psychiatric disorders, or traumatic brain injury were recruited (16 male, 14 female, age 18 to 32 years). T1-weighted structural MRI scans were used to derive estimates of total intracranial volume, and hippocampal and amygdala gray matter volume using FreeSurfer. To relate brain structure to Gray’s BIS, participants completed the Sensitivity to Punishment questionnaire. They also completed questionnaires assessing other measures potentially associated with hippocampal volume (Beck Depression Inventory, Negative Life Experience Survey), and two other measures of anxiety (Spielberger Trait Anxiety Inventory and the Beck Anxiety Inventory). Results: We found that high scores on the Sensitivity to Punishment scale were positively associated with hippocampal volume, and that this phenomenon was lateralized to the right side. In other words, greater levels of behavioural inhibition (BIS) were positively associated with right hippocampal volume. Conclusions: Our data suggest that hippocampal volume is related to the cognitive and affective dimensions of anxiety indexed by the Sensitivity to Punishment, and support the idea that morphological differences in the hippocampal formation may be associated with behavioural inhibition contributions to anxiety