Search results

Partitioned analysis is an increasingly popular approach for modeling complex systems with behaviors governed by multiple, interdependent physical phenomena. Yielding accurate representations of reality from partitioned models depends on the availability of all necessary constituent models representing relevant physical phenomena. However, there are many engineering problems where one or more of the constituents may be unavailable because of lack of knowledge regarding the underlying principles governing the behavior or the inability to experimentally observe the constituent behavior in an isolated manner through separate-effect experiments. This study aims to enable partitioned analysis in such situations with an incomplete representation of the full system by inferring the behavior of the missing constituent.

This paper presents a statistical method for inverse analysis infer missing constituent physics. The feasibility of the method is demonstrated using a physics-based visco-plastic self-consistent (VPSC) model that represents the mechanics of slip and twinning behavior in 5182 aluminum alloy. However, a constituent model to carry out thermal analysis representing the dependence of hardening parameters on temperature is unavailable. Using integral-effect experimental data, the proposed approach is used to infer an empirical constituent model, which is then coupled with VPSC to obtain an experimentally augmented partitioned model representing the thermo-mechanical properties of 5182 aluminum alloy.

Results demonstrate the capability of the method to enable model predictions dependent upon relevant operational conditions. The VPSC model is coupled with the empirical constituent, and the newly enabled thermal-dependent predictions are compared with experimental data.

The method developed in this paper enables the empirical inference of a functional representation of input parameter values in lieu of a missing constituent model. Through this approach, development of partitioned models in the presence of uncertainty regarding a constituent model is made possible.

Salford based paint manufacturer, Granyte Surface Coatings plc, has announced several key board changes, took effect from 1st June. Having attained the age of 60yrs, William Junner will retire as managing director, continuing as executive chairman with speical responsibility for overseas development and acquisitions strategy. His previous role will be undertaken by Gordon Hall, the present Group sales director. That position, in turn, will be filled by the current Southern area sales manager, Brian Williams.

This study aims to better understand how students’ academic strains and multilevel strengths relate to their math achievement, with a particular emphasis on underrepresented students of color and girls given the need to broaden science, technology, engineering and math (STEM) participation for these groups.

National Education Longitudinal Study of 1988 data was used for a historical examination of the various student academic strains and multilevel strengths that relate to math achievement in high school. T-tests and chi-square tests were conducted to examine differences in strains and strengths across policy-relevant student subgroups. Ordinary least squares (OLS) regression was used to examine how students’ strains and strengths related to their math achievement and the relative importance of each of these factors.

The findings suggest that both the academic strains and multilevel strengths that students’ experience in middle school are related to their high school math achievement and the prevalence of these factors varies across different policy-relevant student subgroups. Furthermore, the relative importance of these factors on achievement differs.

Studies which focus on either students’ academic challenges or their adaptive strengths fall short of a more nuanced discussion about how both factors relate to math outcomes. This study addresses this limitation and emphasizes that stakeholders who are interested in STEM diversity should consider holistic strategies for alleviating gender and racial/ethnic discrepancies in secondary math achievement.

Studies of patient satisfaction are regarded by many as the most important way to obtain patients′ views. To date, relatively few studies have focussed specifically on dissatisfaction. Concerns have been expressed about the validity of the concept of satisfaction. Dissatisfaction, however, has received little attention since it has been assumed to be the opposite of satisfaction and thus already defined. Therefore, a series of assumptions have also been made about dissatisfaction, which may or may not compromise its validity or usefulness. The aim of this review is to clarify the concept of dissatisfaction by examining what studies of patient satisfaction can and cannot tell us about dissatisfaction; identifying assumptions; and finally by suggesting how research might best be oriented to accommodate the complexity of patient experiences.