Application of analysis techniques for low frequency interior noise and vibration of commercial aircraft

Finite element analysis (FEA), statistical energy analysis (SEA), and a power flow method (computer program PAIN) were used to assess low frequency interior noise associated with advanced propeller installations. FEA and SEA models were used to predict cabin noise and vibration and evaluate suppression concepts for structure-borne noise associated with the shaft rotational frequency and harmonics (less than 100 Hz). SEA and PAIN models were used to predict cabin noise and vibration and evaluate suppression concepts for airborne noise associated with engine radiated propeller tones. Both aft-mounted and wing-mounted propeller configurations were evaluated. Ground vibration test data from a 727 airplane modified to accept a propeller engine were used to compare with predictions for the aft-mounted propeller. Similar data from the 767 airplane was used for the wing-mounted comparisons

Evaluation of analysis techniques for low frequency interior noise and vibration of commercial aircraft

The application of selected analysis techniques to low frequency cabin noise associated with advanced propeller engine installations is evaluated. Three design analysis techniques were chosen for evaluation including finite element analysis, statistical energy analysis (SEA), and a power flow method using element of SEA (computer program Propeller Aircraft Interior Noise). An overview of the three procedures is provided. Data from tests of a 727 airplane (modified to accept a propeller engine) were used to compare with predictions. Comparisons of predicted and measured levels at the end of the first year's effort showed reasonable agreement leading to the conclusion that each technique had value for propeller engine noise predictions on large commercial transports. However, variations in agreement were large enough to remain cautious and to lead to recommendations for further work with each technique. Assessment of the second year's results leads to the conclusion that the selected techniques can accurately predict trends and can be useful to a designer, but that absolute level predictions remain unreliable due to complexity of the aircraft structure and low modal densities

Pharmacological manipulation of L-carnitine transport into L6 cells with stable overexpression of human OCTN2

Abstract.: The high-affinity Na+-dependent carnitine transporter OCTN2 (SLC22A5) has a high renal expression and reabsorbs most filtered carnitine. To gain more insight into substrate specificity of OCTN2, we overexpressed hOCTN2 in L6 cells and characterized the structural requirements of substances acting as human OCTN2 (hOCTN2) inhibitors. A 1905-bp fragment containing the hOCTN2 complete coding sequence was introduced into the pWpiresGFP vector, and L6 cells were stably transduced using a lentiviral system. The transduced L6 cells revealed increased expression of hOCTN2 on the mRNA, protein and functional levels. Structural requirements for hOCTN2 inhibition were predicted in silico and investigated in vitro. Essential structural requirements for OCTN2 inhibition include a constantly positively charged nitrogen atom and a carboxyl, nitrile or ester group connected by a 2-4-atom linker. Our cell system is suitable for studying in vitro interactions with OCTN2, which can subsequently be investigated in viv

Remote sensing of vegetation fires and its contribution to a fire management information system

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the type of information remote sensing can provide to the fire community. It considers first fire management information needs in the context of fire management information system. An introduction to remote sensing then precedes the description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate how the information can be used in practice

Social evaluation at a distance – facets of stereotype content about student groups in higher distance education

In the academic domain, belonging to a negatively stereotyped group can impair performance and peer relationships. In higher distance education, stereotypes may be particularly influential as face-to-face contact is limited and non-traditional students who are at risk of being stereotyped are overrepresented. Still, research on stereotypes in higher distance education is sparse. The current research addresses this gap by investigating the Big Two of social perception (warmth, competence) and subordinate facets (friendliness, morality, assertiveness, ability, conscientiousness) in the context of higher distance education. It tests a) how well models with warmth/competence or the facets fit the data, b) whether stereotypes in higher distance education depend on the student group, and c) how the Big Two and subordinate facets predict intergroup emotions and behavioral intentions in higher distance education. An online survey with N = 626 students (74% female) of a large distance university showed that a measurement model with four facets (i.e., friendliness, morality, ability, conscientiousness) reveals adequate model fit for 12 student groups. Perceived stereotypes were positive for female students, older students, and students with children. However, migrant as well as younger students were perceived negatively. Across groups, stereotype content facets predicted intergroup emotions and behavioral intentions of facilitation or harm. Implications for the influence of negative stereotypes in higher distance education are discussed