Computer program for solving laminar, transitional, or turbulent compressible boundary-layer equations for two-dimensional and axisymmetric flow

A numerical algorithm and computer program are presented for solving the laminar, transitional, or turbulent two dimensional or axisymmetric compressible boundary-layer equations for perfect-gas flows. The governing equations are solved by an iterative three-point implicit finite-difference procedure. The software, program VGBLP, is a modification of the approach presented in NASA TR R-368 and NASA TM X-2458, respectively. The major modifications are: (1) replacement of the fourth-order Runge-Kutta integration technique with a finite-difference procedure for numerically solving the equations required to initiate the parabolic marching procedure; (2) introduction of the Blottner variable-grid scheme; (3) implementation of an iteration scheme allowing the coupled system of equations to be converged to a specified accuracy level; and (4) inclusion of an iteration scheme for variable-entropy calculations. These modifications to the approach presented in NASA TR R-368 and NASA TM X-2458 yield a software package with high computational efficiency and flexibility. Turbulence-closure options include either two-layer eddy-viscosity or mixing-length models. Eddy conductivity is modeled as a function of eddy viscosity through a static turbulent Prandtl number formulation. Several options are provided for specifying the static turbulent Prandtl number. The transitional boundary layer is treated through a streamwise intermittency function which modifies the turbulence-closure model. This model is based on the probability distribution of turbulent spots and ranges from zero to unity for laminar and turbulent flow, respectively. Several test cases are presented as guides for potential users of the software

Validity of very short answer versus single best answer questions for undergraduate assessment

Background Single Best Answer (SBA) questions are widely used in undergraduate and postgraduate medical examinations. Selection of the correct answer in SBA questions may be subject to cueing and therefore might not test the student’s knowledge. In contrast to this artificial construct, doctors are ultimately required to perform in a real-life setting that does not offer a list of choices. This professional competence can be tested using Short Answer Questions (SAQs), where the student writes the correct answer without prompting from the question. However, SAQs cannot easily be machine marked and are therefore not feasible as an instrument for testing a representative sample of the curriculum for a large number of candidates. We hypothesised that a novel assessment instrument consisting of very short answer (VSA) questions is a superior test of knowledge than assessment by SBA. Methods We conducted a prospective pilot study on one cohort of 266 medical students sitting a formative examination. All students were assessed by both a novel assessment instrument consisting of VSAs and by SBA questions. Both instruments tested the same knowledge base. Using the filter function of Microsoft Excel, the range of answers provided for each VSA question was reviewed and correct answers accepted in less than two minutes. Examination results were compared between the two methods of assessment. Results Students scored more highly in all fifteen SBA questions than in the VSA question format, despite both examinations requiring the same knowledge base. Conclusions Valid assessment of undergraduate and postgraduate knowledge can be improved by the use of VSA questions. Such an approach will test nascent physician ability rather than ability to pass exams

Evaluation of moire techniques for wind tunnel metrology

The development of a moire technique suitable for the analysis of object deflections in a cryogenically cooled, transonic wind tunnel is described. The operating environment for the wind tunnel has a temperature range of 77 to 3390 k, pressure to 91390 Kgs/sq m, and noise to 150 dB SPL. Efforts were made to accomplish the following: to demonstrate projection moire as it would be used to study structural deflections; to use optical processing to multiply the sensitivity of the moire; and to investigate a system design based on the requirements of the wind tunnel geometry

Cognitive barriers during monitoring-based commissioning of buildings

Monitoring-based commissioning (MBCx) is a continuous building energy management process used to optimize energy performance in buildings. Although monitoring-based commissioning (MBCx) can reduce energy waste by up to 20%, many buildings still underperform due to issues such as unnoticed system faults and inefficient operational procedures. While there are technical barriers that impede the MBCx process, such as data quality, the focuses of this paper are the non-technical, behavioral and organizational, barriers that contribute to issues initiating and implementing MBCx. In particular, this paper discusses cognitive biases, which can lead to suboptimal outcomes in energy efficiency decisions, resulting in missed opportunities for energy savings. This paper provides evidence of cognitive biases in decisions during the MBCx process using qualitative data from over 40 public and private sector organizations. The results describe barriers resulting from cognitive biases, listed in descending order of occurrence, including: risk aversion, social norms, choice overload, status quo bias, information overload, professional bias, and temporal discounting. Building practitioners can use these results to better understand potential cognitive biases, in turn allowing them to establish best practices and make more informed decisions. Researchers can use these results to empirically test specific decision interventions and facilitate more energy efficient decisions

Modelling primary health care use: a panel zero inflated interval regression approach

We introduce the (panel) zero-inflated interval regression (ZIIR) model, to investigate GP visits using individual-level data from the British Household Panel Survey. The ZIIR is particularly suitable for this application as it jointly estimates the probability of visiting the GP and then, conditional on visiting, the frequency of visits (defined by given numerical intervals in the data). The results show that different socio-economic factors influence the probability of visiting the GP and the frequency of visits

Tools made of ice facilitate forming of soft, sticky materials

Tools made of ice facilitate the forming or shaping of materials that are soft and sticky in the uncured state. The low-temperature of the ice slows the curing of the material, extending the working time available before setup. Handling problems are eliminated because the material does not adhere to the tool, and the melting ice serves as a lubricant

Atlantic Exchange: Case Studies of Housing and Community Redevelopment in the United States and the United Kingdom

Examines lessons learned from community redevelopment initiatives in Birmingham, England, and Chicago. Explores physical, managerial, and demographic changes and issues of place identity, community cohesion, and the communities' place in city initiatives

Deep learning with convolutional neural networks for decoding and visualization of EEG pathology

We apply convolutional neural networks (ConvNets) to the task of distinguishing pathological from normal EEG recordings in the Temple University Hospital EEG Abnormal Corpus. We use two basic, shallow and deep ConvNet architectures recently shown to decode task-related information from EEG at least as well as established algorithms designed for this purpose. In decoding EEG pathology, both ConvNets reached substantially better accuracies (about 6% better, ~85% vs. ~79%) than the only published result for this dataset, and were still better when using only 1 minute of each recording for training and only six seconds of each recording for testing. We used automated methods to optimize architectural hyperparameters and found intriguingly different ConvNet architectures, e.g., with max pooling as the only nonlinearity. Visualizations of the ConvNet decoding behavior showed that they used spectral power changes in the delta (0-4 Hz) and theta (4-8 Hz) frequency range, possibly alongside other features, consistent with expectations derived from spectral analysis of the EEG data and from the textual medical reports. Analysis of the textual medical reports also highlighted the potential for accuracy increases by integrating contextual information, such as the age of subjects. In summary, the ConvNets and visualization techniques used in this study constitute a next step towards clinically useful automated EEG diagnosis and establish a new baseline for future work on this topic.Comment: Published at IEEE SPMB 2017 https://www.ieeespmb.org/2017