Determination of stresses in gas-turbine disks subjected to plastic flow and creep

A finite-difference method previously presented for computing elastic stresses in rotating disks is extended to include the computation of the disk stresses when plastic flow and creep are considered. A finite-difference method is employed to eliminate numerical integration and to permit nontechnical personnel to make the calculations with a minimum of engineering supervision. Illustrative examples are included to facilitate explanation of the procedure by carrying out the computations on a typical gas-turbine disk through a complete running cycle. The results of the numerical examples presented indicate that plastic flow markedly alters the elastic-stress distribution

Empirical mode constants for calculating frequencies of axial-flow compressor blades

The vibration characteristics of a group of axial-flow compressor blades of similar geometry were investigated. Empirical-mode constants were determined for the first three bending and torsional modes. A comparison of experimentally determined frequencies of a second group of blades with frequencies computed using these mode constants showed that the computed values were correct within 10 percent. The approximate limiting ratios of depth to chord and length to chord below which these constants could not be used to compute the natural frequencies were also found experimentally

Sins of Omission

Little is known about the relative incidence of serious errors of omission versus errors of commission. Objective : To identify the most common substantive medical errors identified by medical record review. Design : Retrospective cohort study. Setting : Twelve Veterans Affairs health care systems in 2 regions. Participants : Stratified random sample of 621 patients receiving care over a 2-year period. Main Outcome Measure : Classification of reported quality problems. Methods : Trained physicians reviewed the full inpatient and outpatient record and described quality problems, which were then classified as errors of omission versus commission. Results : Eighty-two percent of patients had at least 1 error reported over a 13-month period. The average number of errors reported per case was 4.7 (95% confidence intervals [CI]: 4.4, 5.0). Overall, 95.7% (95% CI: 94.9%, 96.4%) of errors were identified as being problems with underuse. Inadequate care for people with chronic illnesses was particularly common. Among errors of omission, obtaining insufficient information from histories and physicals (25.3%), inadequacies in diagnostic testing (33.9%), and patients not receiving needed medications (20.7%) were all common. Out of the 2,917 errors identified, only 27 were rated as being highly serious, and 26 (96%) of these were errors of omission. Conclusions : While preventing iatrogenic injury resulting from medical errors is a critically important part of quality improvement, we found that the overwhelming majority of substantive medical errors identifiable from the medical record were related to people getting too little medical care, especially for those with chronic medical conditions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74567/1/j.1525-1497.2005.0152.x.pd

It is time to talk about people: a human-centered healthcare system

Examining vulnerabilities within our current healthcare system we propose borrowing two tools from the fields of engineering and design: a) Reason's system approach [1] and b) User-centered design [2,3]. Both approaches are human-centered in that they consider common patterns of human behavior when analyzing systems to identify problems and generate solutions. This paper examines these two human-centered approaches in the context of healthcare. We argue that maintaining a human-centered orientation in clinical care, research, training, and governance is critical to the evolution of an effective and sustainable healthcare system

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development