Production and characterization of bamboo and sisal fiber reinforced hybrid composite for interior automotive body application

Abstract Composite materials have high strength to weight ratio with low density and high stiffness to weight, high strength ratios, and high fatigue strength to weight ratio compared to traditional engineering materials making them find wide applications in structural constructions. When the lightweight composite materials which are made of lightweight natural fibres are used in automotive application, the fuel economy of the vehicle improves reducing the related harmful emissions. The aim of this research is to develop and characterize the performance of sisal and bamboo reinforced polyester hybrid composite (BSFRHC) with different fibre orientation of sisal and unidirectional (UD) bamboo fibre. Next, BSFRHC was fabricated with 20% total fibre volume fraction. Of this total fibre volume, the composite is fabricated in 3:1 bamboo to sisal fibre ratio using hand lay-up technique. Then tensile, compressive, impact and flexural tests were carried out. In general, it is concluded that as varying fiber orientation, the tensile strength varies. The higher tensile strength is observed with 0° fibre orientation of bamboo/sisal fiber reinforced hybrid composite. From compressive strength of the hybrid composite reinforced with bamboo/sisal fibre, it is observed that the 0°-fibre orientation composite is exhibiting higher compressive strength than 90° fibre orientation composite and bidirectional (0°/90°) fibre orientation composite. Unidirectional 90° fibre orientation was found to have a higher tensile and flexural strength whereas unidirectional 90° and bidirectional (0°/90°) fibre orientation nearly have the same value of tensile strength, whereas bidirectional (0°/90°) was found to be having higher flexural strength than unidirectional 90° fibre orientation. Impact analysis of vehicle internal door panel made of BSFRHC was done using ANSYS Software. Furthermore, it is found that the bamboo and sisal fibre reinforced hybrid composite in unidirectional 0° has the potential to be used for automotive interior part application

Experimental investigation on characteristics of sisal fiber as composite material for light vehicle body applications

Abstract Sisal fiber composites became attractive due to their high specific strength, lightweight and biodegradability. The aim of this work is to examine characteristics of sisal fiber as composite material for light body vehicles on experimental basis. Composite materials prepared using biodegradable natural fibers are found to be most promising materials which can be used in vehicle body which results in reduction of overall weight of the vehicle. In this work sisal fiber was used. Sisal fiber was extracted using knife from the sisal plant leaves collected from Ethiopian highland. To remove cellulosic matter and improve surface roughness of the sisal fiber, it was immersed in sodium hydroxide solution for 24 h. The specimen of composite material is prepared using the general purpose resin as a matrix, the hardener and the sisal fiber as a reinforcement material with the fiber orientation of 00, ± 450, 00 & 900 by using experimental (hand layup fabrication technique). The specimen was prepared and tested as per ECAE and ASTM standard. From the test results it was found that sisal fiber composite is a good light weight replacement for conventional materials in vehicle body applications. From the experiment result it was observed that different orientation of fiber has shown enhanced mechanical properties of the sisal fiber composite material

Gas Exchange Of Hg Over Wetlands, Effect Of Biochar And Activated Carbon On Hg Emissions From Soil, And Seasonal Concentrations Of Hg In Rain

Mercury (Hg) is a global pollutant with human-health and ecological impacts. Gaseous Hg exchange between the atmosphere and aquatic or terrestrial surfaces serves as an important, but not well understood, route for Hg to enter and exit ecosystems. To better understand the role of gaseous Hg exchange in the biogeochemical cycling of Hg, we investigated Hg0 fluxes over natural wetlands (Sky Lake) and artificial wetlands (UM Field Station) using a dynamic flux chamber and an Hg vapor analyzer based on atomic fluorescence (Chapter 1). We also examined the effect of activated carbon and biochar on Hg emissions from soils for potential remediation purposes (Chapter 2). Finally, we studied the concentration of total-Hg in rain in Oxford, Mississippi, as a function of season and cloud-type (Chapter 3). Mercury emission fluxes from soils varied diurnally, with higher fluxes during the day, and lower and more stable fluxes during the night. Emission of Hg was correlated (p\u3c0.05) with solar radiation for both soil (r=0.81) and water (r=0.95). Mean ambient levels of total gaseous mercury (TGM) at the Field Station and Sky Lake were 1.57 ± 0.67ng m-3 h-1 and 1.23 ± 0.58ng m-3 h-1, respectively. Mercury emission was generally greater from terrestrial (soil) surfaces compared to aquatic (water) surfaces. For example, the mean flux at the Field Station was 4.5ng m-3 h-1 over soil versus 2.3ng m-3 h-1over water during the same period. Emission of Hg from soils was greatly reduced when the soil was mixed with biochar or activated carbon at 5% weight. We observed that a 1-2% sorbent-soil ratio appears to be the most cost-effective approach for potential remediation purposes. While reduction in Hg emissions was size-dependent with the greatest reduction for the finest fraction (\u3c125?m), the larger size-fraction and crude fraction also reduced soil-Hg emissions. For biochar, the mean Hg flux was reduced from 0.70ng m-3 h-1 to -0.86ng m-3 h-1 indicating that not only were emissions from the soil decreased but also that Hg in the ambient air was being adsorbed on the biochar. Similarly, activated carbon changed the Hg flux from a net emission to a net deposition. These results show that amending soils with these sorbents can be effective to minimize Hg emissions from contaminated soils. Concentrations of total-Hg in rain from Oxford, Mississippi were greater (p\u3c0.05) in the spring and summer during thunderstorms (38 ± 10pg/g) compared to the fall and winter during non-thunderstorms (6.7 ± 3.9pg/g). This supports the hypothesis that cumulonimbus (thunderstorm) clouds, which reach higher altitudes, are effective at scavenging gaseous oxidized Hg species that accumulate in the upper troposphere

Evaluation of binder grades on rutting performance

Asphalt mixes that have a good history of resisting rutting in posted speed applications may not perform well in intersections, climbing lanes, truck weigh stations, and other slow speed areas. The West Virginia Division of Highways, WVDOH, has implemented the Performance Grade binder specifications for all paving projects and Superpave for high volume road projects. The standard binder specified in the state is a PG 64-22; for high volume roads a PG 70-22 is specified. These binders appear to be working well for most projects in the state. The Superpave guidelines have provision for increasing the binder grade by one level to accommodate slow moving traffic. Prior to 2002, the WVDOH had not implemented this option. In 2002, the WVDOH elected to use a Superpave mix with a PG 76-22 binder to resolve maintenance issues at an intersection near Fort Gay, WV.;The objective of this research was to evaluate the rutting potential of the asphalt concrete mixes prepared with three binder grades. The research included mix designs for the base course and the wearing course of the pavement. The base course was a 37.5 mm mix with limestone aggregates and the wearing course was a 12.5 mm mix with predominantly blast furnace slag aggregates.;The three different binders were compared by making specimens with each of the two mix designs. The Asphalt Pavement Analyzer, APA, was used to evaluate rutting performance of the gyratory compacted samples. The statistical analysis of the rut depths provides evidence that the PG 76-22 polymer-modified binder performs better than PG 70-22 and PG 64-22 binder

Impact of COVID-19 lockdown on the social media usage among different age groups in Hyderabad, India: A questionnaire-based community Study

The emergence and rapid spread of SARS-CoV-2 across the globe has caused a state of panic and chaos. Self-quarantine and lockdowns have been implemented in many countries leaving the public homebound. On one hand social media being a prime source of information, it could have a substantial contribution in causing unnecessary apprehension and fear in the public due to the speculations and misinformation, while on the other hand the unexpected event of lockdown resulted in a spurt of social media usage. The adverse effect of social media on psychological well-being, academic performance, socializing skills, interpersonal relationship and parenting were recorded by a number of studies in the past. It is imperative to be mindful of the content being watched and the time spent on social media. The study aims to understand the variation in social media usage in different age groups in the people of Hyderabad, India due to the COVID-19 pandemic. The survey was conducted through a questionnaire that was created using Google forms. The study shows that the social media usage has significantly increased in the people of Hyderabad, India during the COVID-19 lockdown. The data shows a correlation between the age groups and variation in social media usage. The increased social media usage is more in the younger age groups below 25 years. The study proves no impact of social media usage on productivity during the quarantin

A Review of Elastic Search: Performance Metrics and challenges

The most important aspect of a search engine is the search. Elastic search is a highly scalable search engine that stores data in a structure, optimized for language based searches. When it comes to using Elastic search, there are lots of metrics engendered. By using Elastic search to index millions of code repositories as well as indexing critical event data, you can satisfy the search needs of millions of users while instantaneously providing strategic operational visions that help you iteratively improve customer service. In this paper we are going to study about Elastic searchperformance metrics to watch, important Elastic search challenges, and how to deal with them. This should be helpful to anyone new to Elastic search, and also to experienced users who want a quick start into performance monitoring of Elastic search

Geographic variation in statin use for complex acute myocardial infarction patients: evidence of effective care?

Reprinted with permission of publisher.BACKGROUND: Despite strong evidence to designate statin use for secondary prevention of cardiovascular disease (CVD) as "effective care," observational studies show that many patients with CVD do not receive statins. This suggests that statin prescribing decisions for complex CVD patients are preference sensitive. OBJECTIVES: The aim of this study was to evaluate local area variation in statin prescribing for subsets of complex patients after acute myocardial infarction (AMI) to assess whether current statin prescribing patterns fit profiles of either "effective care" or "preference-sensitive care." RESEARCH DESIGN AND SUBJECTS: This was a retrospective cohort study of 124,618 Medicare patients with fee-for-service parts A, B, and D benefits who were hospitalized with AMI in 2008 or 2009 with no evidence of AMI in the past 12 months. MEASURES:Patient complexity was defined by the presence of diabetes, heart failure, and chronic kidney disease in the year before AMI admission. Local area practice styles for "no statin," "lower-intensity statins," and "high-intensity statins" were measured using the driving area for clinical care method. Statin prescribing rates for complex patient subsets were contrasted across patients grouped by local areas practice styles. RESULTS: Lower statin treatment rates were observed for patients with complex conditions, especially among those with heart failure. However, substantial local area variation in statin prescribing is observed across all complex patient groups. CONCLUSIONS: Despite guidelines promoting the use of statins for secondary prevention for CVD patients, substantial local area variation suggests that patient and provider beliefs and preferences weigh heavily in statin prescribing decisions.This project was supported by an Agency for Healthcare Research and Quality grant (1R21HS019574-01) under the American Recovery and Reinvestment Act of 2009

When Zebras Run with Horses: The Diagnostic Dilemma of Acute Aortic Dissection Complicated by Myocardial Infarction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72234/1/j.1540-8183.2002.tb01107.x.pd

Using machine learning to model dose–response relationships

Rationale, aims and objectivesEstablishing the relationship between various doses of an exposure and a response variable is integral to many studies in health care. Linear parametric models, widely used for estimating dose–response relationships, have several limitations. This paper employs the optimal discriminant analysis (ODA) machine‐learning algorithm to determine the degree to which exposure dose can be distinguished based on the distribution of the response variable. By framing the dose–response relationship as a classification problem, machine learning can provide the same functionality as conventional models, but can additionally make individual‐level predictions, which may be helpful in practical applications like establishing responsiveness to prescribed drug regimens.MethodUsing data from a study measuring the responses of blood flow in the forearm to the intra‐arterial administration of isoproterenol (separately for 9 black and 13 white men, and pooled), we compare the results estimated from a generalized estimating equations (GEE) model with those estimated using ODA.ResultsGeneralized estimating equations and ODA both identified many statistically significant dose–response relationships, separately by race and for pooled data. Post hoc comparisons between doses indicated ODA (based on exact P values) was consistently more conservative than GEE (based on estimated P values). Compared with ODA, GEE produced twice as many instances of paradoxical confounding (findings from analysis of pooled data that are inconsistent with findings from analyses stratified by race).ConclusionsGiven its unique advantages and greater analytic flexibility, maximum‐accuracy machine‐learning methods like ODA should be considered as the primary analytic approach in dose–response applications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134965/1/jep12573_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134965/2/jep12573.pd