Experimental and Computational Analysis of Low-Velocity Impact on Carbon-, Glass- and Mixed-Fiber Composite Plates

One of the problems with composites is their weak impact damage resistance and post-impact mechanical properties. Composites are prone to delamination damage when impacted by low-speed projectiles because of the weak through-thickness strength. To combat the problem of delamination damage, composite parts are often over-designed with extra layers. However, this increases the cost, weight, and volume of the composite and, in some cases, may only provide moderate improvements to impact damage resistance. The selection of the optimal parameters for composite plates that give high impact resistance under low-velocity impact loads should consider several factors related to the properties of the materials as well as to how the composite product is manufactured. To obtain the desired impact resistance, it is essential to know the interrelationships between these parameters and the energy absorbed by the composite. Knowing which parameters affect the improvement of the composite impact resistance and which parameters give the most significant effect are the main issues in the composite industry. In this work, the impact response of composite laminates with various stacking sequences and resins was studied with the Instron 9250G drop-tower to determine the energy absorption. Three types of composites were used: carbon-fiber, glass-fiber, and mixed-fiber composite laminates. Also, these composites were characterized by different stacking sequences and resin types. The effect of several composite structural parameters on the absorbed energy of composite plates is studied. A finite element model was then used to find an optimized design with improved impact resistance based on the best attributes found from the experimental testing

Gender disparities in the presentation, management and outcomes of acute coronary syndrome patients: data from the 2nd Gulf Registry of Acute Coronary Events (Gulf RACE-2).

BACKGROUND: Gender-related differences in mortality of acute coronary syndrome (ACS) have been reported. The extent and causes of these differences in the Middle-East are poorly understood. We studied to what extent difference in outcome, specifically 1-year mortality are attributable to demographic, baseline clinical differences at presentation, and management differences between female and male patients. METHODOLOGY/PRINCIPAL FINDINGS: Baseline characteristics, treatment patterns, and 1-year mortality of 7390 ACS patients in 65 hospitals in 6 Arabian Gulf countries were evaluated during 2008-2009, as part of the 2nd Gulf Registry of Acute Coronary Events (Gulf RACE-2). Women were older (61.3±11.8 vs. 55.6±12.4; P<0.001), more overweight (BMI: 28.1±6.6 vs. 26.7±5.1; P<0.001), and more likely to have a history of hypertension, hyperlipidemia or diabetes. Fewer women than men received angiotensin-converting enzyme inhibitors (ACE), aspirin, clopidogrel, beta blockers or statins at discharge. They also underwent fewer invasive procedures including angiography (27.0% vs. 34.0%; P<0.001), percutaneous coronary intervention (PCI) (10.5% vs. 15.6%; P<0.001) and reperfusion therapy (6.9% vs. 20.2%; P<0.001) than men. Women were at higher unadjusted risk for in-hospital death (6.8% vs. 4.0%, P<0.001) and heart failure (HF) (18% vs. 11.8%, P<0.001). Both 1-month and 1-year mortality rates were higher in women than men (11% vs. 7.4% and 17.3% vs. 11.4%, respectively, P<0.001). Both baseline and management differences contributed to a worse outcome in women. Together these variables explained almost all mortality disparities. CONCLUSIONS/SIGNIFICANCE: Differences between genders in mortality appeared to be largely explained by differences in prognostic variables and management patterns. However, the origin of the latter differences need further study

In-hospital outcomes and 1-month and 1-year post discharge mortality of the study cohort by gender (n = 7930).

<p>Figures in parentheses are percentages.</p

Variables in model IV, and their effects on mortality.

<p>ORs for variables with multiple levels (country, diagnosis, and predominant symptoms) are not shown. The variables that were dropped out of the multivariable logistic regression using the stepwise-backward elimination method included: smoking, BMI, history of hypertension and hyperlipidaemia, clopidogrel as discharge medication, PCI, and CABG.</p>*<p>Predominant presenting symptoms includes: ischemic type chest pain, atypical chest pain, dyspnea, fatigue, loss of consciousness, cardiac arrest/aborted sudden death, palpitation and other symptoms.</p><p>Abbreviations: OR, odds ratio; CI, confidence interval; BB, beta-blockers; CCB, calcium channel blockers; ACE, angiotensin-converting enzyme inhibitors; AIIRB, angiotensin II receptor blockers.</p

Baseline characteristics of patients stratified by gender (n = 7930).

<p>Figures in parentheses are percentages and continuous variables are shown as mean±SD.</p><p>Abbreviations: SD, standard deviation; BMI, body mass index; CAD, coronary artery disease; MI, myocardial infarction; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft; CHF, congestive heart failure; STEMI, ST elevation myocardial infarction; NSTEMI, non-ST-elevation myocardial infarction; UA, unstable angina.</p>*<p>Killip class (scale I–IV) a system used to stratify the severity of left ventricular dysfunction and determines clinical status of patients post myocardial infarction (MI).</p><p>Killip classification:</p><p>Class 1: No rales, no 3rd heart sound.</p><p>Class 2: Rales in <1/2 lung field or presence of a 3rd heart sound.</p><p>Class 3: Rales in >1/2 lung field–pulmonary edema.</p><p>Class 4: Cardiogenic shock–determined clinically.</p

Treatment on admission and at discharge of the study cohort stratified according to gender (n = 7930).

<p>Figures in parentheses are percentages. Abbreviations: BB, beta-blockers; CCB, calcium channel blockers; ACE, angiotensin-converting enzyme inhibitors; AIIRB, angiotensin II receptor blockers; OHA, oral hypoglycemic agents; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft.</p