Search results for: non-destructive and destructive testing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3381

Search results for: non-destructive and destructive testing

2151 Experimenting with Error Performance of Systems Employing Pulse Shaping Filters on a Software-Defined-Radio Platform

Authors: Chia-Yu Yao

Abstract:

This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: pulse-shaping filters, FIR filters, jittering, QAM

Procedia PDF Downloads 337
2150 Verification of Low-Dose Diagnostic X-Ray as a Tool for Relating Vital Internal Organ Structures to External Body Armour Coverage

Authors: Natalie A. Sterk, Bernard van Vuuren, Petrie Marais, Bongani Mthombeni

Abstract:

Injuries to the internal structures of the thorax and abdomen remain a leading cause of death among soldiers. Body armour is a standard issue piece of military equipment designed to protect the vital organs against ballistic and stab threats. When configured for maximum protection, the excessive weight and size of the armour may limit soldier mobility and increase physical fatigue and discomfort. Providing soldiers with more armour than necessary may, therefore, hinder their ability to react rapidly in life-threatening situations. The capability to determine the optimal trade-off between the amount of essential anatomical coverage and hindrance on soldier performance may significantly enhance the design of armour systems. The current study aimed to develop and pilot a methodology for relating internal anatomical structures with actual armour plate coverage in real-time using low-dose diagnostic X-ray scanning. Several pilot scanning sessions were held at Lodox Systems (Pty) Ltd head-office in South Africa. Testing involved using the Lodox eXero-dr to scan dummy trunk rigs at various degrees and heights of measurement; as well as human participants, wearing correctly fitted body armour while positioned in supine, prone shooting, seated and kneeling shooting postures. The verification of sizing and metrics obtained from the Lodox eXero-dr were then confirmed through a verification board with known dimensions. Results indicated that the low-dose diagnostic X-ray has the capability to clearly identify the vital internal structures of the aortic arch, heart, and lungs in relation to the position of the external armour plates. Further testing is still required in order to fully and accurately identify the inferior liver boundary, inferior vena cava, and spleen. The scans produced in the supine, prone, and seated postures provided superior image quality over the kneeling posture. The X-ray-source and-detector distance from the object must be standardised to control for possible magnification changes and for comparison purposes. To account for this, specific scanning heights and angles were identified to allow for parallel scanning of relevant areas. The low-dose diagnostic X-ray provides a non-invasive, safe, and rapid technique for relating vital internal structures with external structures. This capability can be used for the re-evaluation of anatomical coverage required for essential protection while optimising armour design and fit for soldier performance.

Keywords: body armour, low-dose diagnostic X-ray, scanning, vital organ coverage

Procedia PDF Downloads 119
2149 Interruption Overload in an Office Environment: Hungarian Survey Focusing on the Factors that Affect Job Satisfaction and Work Efficiency

Authors: Fruzsina Pataki-Bittó, Edit Németh

Abstract:

On the one hand, new technologies and communication tools improve employee productivity and accelerate information and knowledge transfer, while on the other hand, information overload and continuous interruptions make it even harder to concentrate at work. It is a great challenge for companies to find the right balance, while there is also an ongoing demand to recruit and retain the talented employees who are able to adopt the modern work style and effectively use modern communication tools. For this reason, this research does not focus on the objective measures of office interruptions, but aims to find those disruption factors which influence the comfort and job satisfaction of employees, and the way how they feel generally at work. The focus of this research is on how employees feel about the different types of interruptions, which are those they themselves identify as hindering factors, and those they feel as stress factors. By identifying and then reducing these destructive factors, job satisfaction can reach a higher level and employee turnover can be reduced. During the research, we collected information from depth interviews and questionnaires asking about work environment, communication channels used in the workplace, individual communication preferences, factors considered as disruptions, and individual steps taken to avoid interruptions. The questionnaire was completed by 141 office workers from several types of workplaces based in Hungary. Even though 66 respondents are working at Hungarian offices of multinational companies, the research is about the characteristics of the Hungarian labor force. The most important result of the research shows that while more than one third of the respondents consider office noise as a disturbing factor, personal inquiries are welcome and considered useful, even if in such cases the work environment will not be convenient to solve tasks requiring concentration. Analyzing the sizes of the offices, in an open-space environment, the rate of those who consider office noise as a disturbing factor is surprisingly lower than in smaller office rooms. Opinions are more diverse regarding information communication technologies. In addition to the interruption factors affecting the employees' job satisfaction, the research also focuses on the role of the offices in the 21st century.

Keywords: information overload, interruption, job satisfaction, office environment, work efficiency

Procedia PDF Downloads 225
2148 Cognitive Weighted Polymorphism Factor: A New Cognitive Complexity Metric

Authors: T. Francis Thamburaj, A. Aloysius

Abstract:

Polymorphism is one of the main pillars of the object-oriented paradigm. It induces hidden forms of class dependencies which may impact software quality, resulting in higher cost factor for comprehending, debugging, testing, and maintaining the software. In this paper, a new cognitive complexity metric called Cognitive Weighted Polymorphism Factor (CWPF) is proposed. Apart from the software structural complexity, it includes the cognitive complexity on the basis of type. The cognitive weights are calibrated based on 27 empirical studies with 120 persons. A case study and experimentation of the new software metric shows positive results. Further, a comparative study is made and the correlation test has proved that CWPF complexity metric is a better, more comprehensive, and more realistic indicator of the software complexity than Abreu’s Polymorphism Factor (PF) complexity metric.

Keywords: cognitive complexity metric, object-oriented metrics, polymorphism factor, software metrics

Procedia PDF Downloads 448
2147 Efficient Moment Frame Structure

Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

Abstract:

A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: modified hybrid joint, repair, seismic loading type, acceptance criteria

Procedia PDF Downloads 515
2146 Serological IgG Testing to Diagnose Alimentary Induced Diseases and Monitoring Efficacy of an Individual Defined Diet in Dogs

Authors: Anne-Margré C. Vink

Abstract:

Background: Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according to ‘Golden Standard’ of elimination efficiency are time-consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated. Method: As we developed Medisynx IgG Human Screening Test ELISA before and the dog’s immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this study, 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring the efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results: The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs(44 out of 47 dogs =93.6%). Conclusion: Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: allergy, canine atopic dermatitis, CAD, food allergens, IgG-ELISA, food-incompatibility

Procedia PDF Downloads 316
2145 Biodiesel Production from Palm Oil Using an Oscillatory Baffled Reactor

Authors: Malee Santikunaporn, Tattep Techopittayakul, Channarong Asavatesanupap

Abstract:

Biofuel production especially that of biodiesel has gained tremendous attention during the last decade due to environmental concerns and shortage in petroleum oil reservoir. This research aims to investigate the influences of operating parameters, such as the alcohol-to-oil molar ratio (4:1, 6:1, and 9:1) and the amount of catalyst (1, 1.5, and 2 wt.%) on the trans esterification of refined palm oil (RPO) in a medium-scale oscillatory baffle reactor.  It has been shown that an increase in the methanol-to-oil ratio resulted in an increase in fatty acid methyl esters (FAMEs) content. The amount of catalyst has an insignificant effect on the FAMEs content. Engine testing was performed on B0 (100 v/v% diesel) and blended fuel or B50 (50 v/v% diesel). Combustion of B50 was found to give lower torque compared to pure diesel. Exhaust gas from B50 was found to contain lower concentration of CO and CO2.

Keywords: biodiesel, palm oil, transesterification, oscillatory baffled reactor

Procedia PDF Downloads 169
2144 Flexible Arm Manipulator Control for Industrial Tasks

Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

Abstract:

This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: distributed model, flexible manipulator, observer, robot control

Procedia PDF Downloads 317
2143 An Enhanced Harmony Search (ENHS) Algorithm for Solving Optimization Problems

Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

Abstract:

Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

Procedia PDF Downloads 454
2142 Influence of Glass Plates Different Boundary Conditions on Human Impact Resistance

Authors: Alberto Sanchidrián, José A. Parra, Jesús Alonso, Julián Pecharromán, Antonia Pacios, Consuelo Huerta

Abstract:

Glass is a commonly used material in building; there is not a unique design solution as plates with a different number of layers and interlayers may be used. In most façades, a security glazing have to be used according to its performance in the impact pendulum. The European Standard EN 12600 establishes an impact test procedure for classification under the point of view of the human security, of flat plates with different thickness, using a pendulum of two tires and 50 kg mass that impacts against the plate from different heights. However, this test does not replicate the actual dimensions and border conditions used in building configurations and so the real stress distribution is not determined with this test. The influence of different boundary conditions, as the ones employed in construction sites, is not well taking into account when testing the behaviour of safety glazing and there is not a detailed procedure and criteria to determinate the glass resistance against human impact. To reproduce the actual boundary conditions on site, when needed, the pendulum test is arranged to be used "in situ", with no account for load control, stiffness, and without a standard procedure. Fracture stress of small and large glass plates fit a Weibull distribution with quite a big dispersion so conservative values are adopted for admissible fracture stress under static loads. In fact, test performed for human impact gives a fracture strength two or three times higher, and many times without a total fracture of the glass plate. Newest standards, as for example DIN 18008-4, states for an admissible fracture stress 2.5 times higher than the ones used for static and wing loads. Now two working areas are open: a) to define a standard for the ‘in situ’ test; b) to prepare a laboratory procedure that allows testing with more real stress distribution. To work on both research lines a laboratory that allows to test medium size specimens with different border conditions, has been developed. A special steel frame allows reproducing the stiffness of the glass support substructure, including a rigid condition used as reference. The dynamic behaviour of the glass plate and its support substructure have been characterized with finite elements models updated with modal tests results. In addition, a new portable impact machine is being used to get enough force and direction control during the impact test. Impact based on 100 J is used. To avoid problems with broken glass plates, the test have been done using an aluminium plate of 1000 mm x 700 mm size and 10 mm thickness supported on four sides; three different substructure stiffness conditions are used. A detailed control of the dynamic stiffness and the behaviour of the plate is done with modal tests. Repeatability of the test and reproducibility of results prove that procedure to control both, stiffness of the plate and the impact level, is necessary.

Keywords: glass plates, human impact test, modal test, plate boundary conditions

Procedia PDF Downloads 303
2141 From By-product To Brilliance: Transforming Adobe Brick Construction Using Meat Industry Waste-derived Glycoproteins

Authors: Amal Balila, Maria Vahdati

Abstract:

Earth is a green building material with very low embodied energy and almost zero greenhouse gas emissions. However, it lacks strength and durability in its natural state. By responsibly sourcing stabilisers, it's possible to enhance its strength. This research draws inspiration from the robustness of termite mounds, where termites incorporate glycoproteins from their saliva during construction. Biomimicry explores the potential of these termite stabilisers in producing bio-inspired adobe bricks. The meat industry generates significant waste during slaughter, including blood, skin, bones, tendons, gastrointestinal contents, and internal organs. While abundant, many meat by-products raise concerns regarding human consumption, religious orders, cultural and ethical beliefs, and also heavily contribute to environmental pollution. Extracting and utilising proteins from this waste is vital for reducing pollution and increasing profitability. Exploring the untapped potential of meat industry waste, this research investigates how glycoproteins could revolutionize adobe brick construction. Bovine serum albumin (BSA) from cows' blood and mucin from porcine stomachs were the chosen glycoproteins used as stabilisers for adobe brick production. Despite their wide usage across various fields, they have very limited utilisation in food processing. Thus, both were identified as potential stabilisers for adobe brick production in this study. Two soil types were utilised to prepare adobe bricks for testing, comparing controlled unstabilised bricks with glycoprotein-stabilised ones. All bricks underwent testing for unconfined compressive strength and erosion resistance. The primary finding of this study is the efficacy of BSA, a glycoprotein derived from cows' blood and a by-product of the beef industry, as an earth construction stabiliser. Adding 0.5% by weight of BSA resulted in a 17% and 41% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Further, adding 5% by weight of BSA led to a 202% and 97% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Moreover, using 0.1%, 0.2%, and 0.5% by weight of BSA resulted in erosion rate reductions of 30%, 48%, and 70% for British adobe bricks, respectively, with a 97% reduction observed for Sudanese adobe bricks at 0.5% by weight of BSA. However, mucin from the porcine stomach did not significantly improve the unconfined compressive strength of adobe bricks. Nevertheless, employing 0.1% and 0.2% by weight of mucin resulted in erosion rate reductions of 28% and 55% for British adobe bricks, respectively. These findings underscore BSA's efficiency as an earth construction stabiliser for wall construction and mucin's efficacy for wall render, showcasing their potential for sustainable and durable building practices.

Keywords: biomimicry, earth construction, industrial waste management, sustainable building materials, termite mounds.

Procedia PDF Downloads 42
2140 Efficacy Testing of a Product in Reducing Facial Hyperpigmentation and Photoaging after a 12-Week Use

Authors: Nalini Kaul, Barrie Drewitt, Elsie Kohoot

Abstract:

Hyperpigmentation is the third most common pigmentary disorder where dermatologic treatment is sought. It affects all ages resulting in skin darkening because of melanin accumulation. An uneven skin tone because of either exposure to the sun (solar lentigos/age spots/sun spots or skin disruption following acne, or rashes (post-inflammatory hyperpigmentation -PIH) or hormonal changes (melasma) can lead to significant psychosocial impairment. Dyschromia is a result of various alterations in biochemical processes regulating melanogenesis. Treatments include the daily use of sunscreen with lightening, brightening, and exfoliating products. Depigmentation is achieved by various depigmenting agents: common examples are hydroquinone, arbutin, azelaic acid, aloesin, mulberry, licorice extracts, kojic acid, niacinamide, ellagic acid, arbutin, green tea, turmeric, soy, ascorbic acid, and tranexamic acid. These agents affect pigmentation by interfering with mechanisms before, during, and after melanin synthesis. While immediate correction is much sought after, patience and diligence are key. Our objective was to assess the effects of a facial product with pigmentation treatment and UV protection in 35 healthy F (35-65y), meeting the study criteria. Subjects with mild to moderate hyperpigmentation and fine lines with no use of skin-lightening products in the last six months or any dermatological procedures in the last twelve months before the study started were included. Efficacy parameters included expert clinical grading for hyperpigmentation, radiance, skin tone & smoothness, fine lines, and wrinkles bioinstrumentation (Corneometer®, Colorimeter®), digital photography and imaging (Visia-CR®), and self-assessment questionnaires. Safety included grading for erythema, edema, dryness & peeling and self-assessments for itching, stinging, tingling, and burning. Our results showed statistically significant improvement in clinical grading scores, bioinstrumentation, and digital photos for hyperpigmentation-brown spots, fine lines/wrinkles, skin tone, radiance, pores, skin smoothness, and overall appearance compared to baseline. The product was also well-tolerated and liked by subjects. Conclusion: Facial hyperpigmentation is of great concern, and treatment strategies are increasingly sought. Clinical trials with both subjective and objective assessments, imaging analyses, and self-perception are essential to distinguish evidence-based products. The multifunctional cosmetic product tested in this clinical study showed efficacy, tolerability, and subject satisfaction in reducing hyperpigmentation and global photoaging.

Keywords: hyperpigmentation; photoaging, clinical testing, expert visual evaluations, bio-instruments

Procedia PDF Downloads 72
2139 An Automated Magnetic Dispersive Solid-Phase Extraction Method for Detection of Cocaine in Human Urine

Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

Abstract:

Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

Procedia PDF Downloads 197
2138 MyAds: A Social Adaptive System for Online Advertisment from Hypotheses to Implementation

Authors: Dana A. Al Qudah, Alexandra I. Critea, Rizik M. H. Al Sayyed, Amer Obeidah

Abstract:

Online advertisement is one of the major incomes for many companies; it has a role in the overall business flow and affects the consumer behavior directly. Unfortunately most users tend to block their ads or ignore them. MyAds is a social adaptive hypermedia system for online advertising and its main goal is to explore how to make online ads more acceptable. In order to achieve such a goal, various technologies and techniques are used. This paper presents a theoretical framework as well as the system architecture for MyAds that was designed based on a set of hypotheses and an exploratory study. The system then was implemented and a pilot experiment was conducted to validate it. The main outcomes suggest that the system has provided personalized ads for users. The main implications suggest that the system can be used for further testing and validating.

Keywords: adaptive hypermedia, e-advertisement, social, hypotheses, exploratory study, framework

Procedia PDF Downloads 403
2137 The Impact of Bitcoin on Stock Market Performance

Authors: Oliver Takawira, Thembi Hope

Abstract:

This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

Procedia PDF Downloads 96
2136 Failure Mode Analysis of a Multiple Layer Explosion Bonded Cryogenic Transition Joint

Authors: Richard Colwell, Thomas Englert

Abstract:

In cryogenic liquefaction processes, brazed aluminum core heat exchangers are used to minimize surface area/volume of the exchanger. Aluminum alloy (5083-H321; UNS A95083) piping must transition to higher melting point 304L stainless steel piping outside of the heat exchanger kettle or cold box for safety reasons. Since aluminum alloys and austenitic stainless steel cannot be directly welded to together, a transition joint consisting of 5 layers of different metals explosively bonded are used. Failures of two of these joints resulted in process shut-down and loss of revenue. Failure analyses, FEA analysis, and mock-up testing were performed by multiple teams to gain a further understanding into the failure mechanisms involved.

Keywords: explosion bonding, intermetallic compound, thermal strain, titanium-nickel Interface

Procedia PDF Downloads 210
2135 Experimental and Numerical Analysis on Enhancing Mechanical Properties of CFRP Adhesive Joints Using Hybrid Nanofillers

Authors: Qiong Rao, Xiongqi Peng

Abstract:

In this work, multi-walled carbon nanotubes (MWCNTs) and graphene nanoplates (GNPs) were dispersed into epoxy adhesive to investigate their synergy effects on the shear properties, mode I and mode II fracture toughness of unidirectional composite bonded joints. Testing results showed that the incorporation of MWCNTs and GNPs significantly improved the shear strength, the mode I and mode II fracture toughness by 36.6%, 45% and 286%, respectively. In addition, the fracture surfaces of the bonding area as well as the toughening mechanism of nanofillers were analyzed. Finally, a nonlinear cohesive/friction coupled model for delamination analysis of adhesive layer under shear and normal compression loadings was proposed and implemented in ABAQUS/Explicit via user subroutine VUMAT.

Keywords: nanofillers, adhesive joints, fracture toughness, cohesive zone model

Procedia PDF Downloads 127
2134 Theoretical and Experimental Bending Properties of Composite Pipes

Authors: Maja Stefanovska, Svetlana Risteska, Blagoja Samakoski, Gari Maneski, Biljana Kostadinoska

Abstract:

Aim of this work is to determine the theoretical and experimental properties of filament wound glass fiber/epoxy resin composite pipes with different winding design subjected under bending. For determination of bending strength of composite samples three point bending tests were conducted according to ASTM D790 standard. Good correlation between theoretical and experimental results has been obtained, where sample No4 has shown the highest value of bending strength. All samples have demonstrated matrix cracking and fiber failure followed by layers delamination during testing. Also, it was found that smaller winding angles lead to an increase in bending stress. From presented results good merger between glass fibers and epoxy resin was confirmed by SEM analysis.

Keywords: bending properties, composite pipe, winding design, SEM

Procedia PDF Downloads 319
2133 An Artificial Intelligence Framework to Forecast Air Quality

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 115
2132 Changes in Postural Stability after Coordination Exercise

Authors: Ivan Struhár, Martin Sebera, Lenka Dovrtělová

Abstract:

The aim of this study was to find out if the special type of exercise with elastic cord can improve the level of postural stability. The exercise programme was conducted twice a week for 3 months. The participants were randomly divided into an experimental group and a control group. The electronic balance board was used for testing of postural stability. All participants trained for 18 hours at the time of experiment without any special form of coordination programme. The experimental group performed 90 minutes plus of coordination exercise. The result showed that differences between pre-test and post-test occurred in the experimental group. It was used the nonparametric Wilcoxon t-test for paired samples (p=0.012; the significance level 95%). We calculated effect size by Cohen´s d. In the experimental group d is 1.96 which indicates a large effect. In the control group d is 0.04 which confirms no significant improvement.

Keywords: balance board, balance training, coordination, stability

Procedia PDF Downloads 386
2131 Evaluation of the Self-Organizing Map and the Adaptive Neuro-Fuzzy Inference System Machine Learning Techniques for the Estimation of Crop Water Stress Index of Wheat under Varying Application of Irrigation Water Levels for Efficient Irrigation Scheduling

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

Abstract:

The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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2130 Evaluation of Iranian Standard for Assessment of Liquefaction Potential of Cohesionless Soils Based on SPT

Authors: Reza Ziaie Moayad, Azam Kouhpeyma

Abstract:

In-situ testing is preferred to evaluate the liquefaction potential in cohesionless soils due to high disturbance during sampling. Although new in-situ methods with high accuracy have been developed, standard penetration test, the simplest and the oldest in-situ test, is still used due to the profusion of the recorded data. This paper reviews the Iranian standard of evaluating liquefaction potential in soils (codes 525) and compares the liquefaction assessment methods based on SPT results on cohesionless soil in this standard with the international standards. To this, methods for assessing liquefaction potential which are presented by Cetin et al. (2004), Boulanger and Idriss (2014) are compared with what is presented in standard 525. It is found that although the procedure used in Iranian standard of evaluating the potential of liquefaction has not been updated according to the new findings, it is a conservative procedure.

Keywords: cohesionless soil, liquefaction, SPT, standard 525

Procedia PDF Downloads 163
2129 Simulation of Non-Crimp 3D Orthogonal Carbon Fabric Composite for Aerospace Applications Using Finite Element Method

Authors: Sh. Minapoor, S. Ajeli, M. Javadi Toghchi

Abstract:

Non-crimp 3D orthogonal fabric composite is one of the textile-based composite materials that are rapidly developing light-weight engineering materials. The present paper focuses on geometric and micro mechanical modeling of non-crimp 3D orthogonal carbon fabric and composites reinforced with it for aerospace applications. In this research meso-finite element (FE) modeling employs for stress analysis in different load conditions. Since mechanical testing of expensive textile carbon composites with specific application isn't affordable, simulation composite in a virtual environment is a helpful way to investigate its mechanical properties in different conditions.

Keywords: woven composite, aerospace applications, finite element method, mechanical properties

Procedia PDF Downloads 453
2128 Geospatial Multi-Criteria Evaluation to Predict Landslide Hazard Potential in the Catchment of Lake Naivasha, Kenya

Authors: Abdel Rahman Khider Hassan

Abstract:

This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands.

Keywords: decision making, geospatial, landslide, multi-criteria, Naivasha

Procedia PDF Downloads 192
2127 Assessing Student Collaboration in Music Ensemble Class: From the Formulation of Grading Rubrics to Their Effective Implementation

Authors: Jason Sah

Abstract:

Music ensemble class is a non-traditional classroom in the sense that it is always a group effort during rehearsal. When measuring student performance ability in class, it is imperative that the grading rubric includes a collaborative skill component. Assessments that stop short of testing students' ability to make music with others undermine the group mentality by elevating individual prowess. Applying empirical and evidence-based methodology, this research develops a grading rubric that defines the criteria for assessing collaborative skill, and then explores different strategies for implementing this rubric in a timely and effective manner. Findings show that when collaborative skill is regularly tested, students gradually shift their attention from playing their own part well to sharing their part with others.

Keywords: assessment, ensemble class, grading rubric, student collaboration

Procedia PDF Downloads 127
2126 Bulk-Density and Lignocellulose Composition: Influence of Changing Lignocellulosic Composition on Bulk-Density during Anaerobic Digestion and Implication of Compacted Lignocellulose Bed on Mass Transfer

Authors: Aastha Paliwal, H. N. Chanakya, S. Dasappa

Abstract:

Lignocellulose, as an alternate feedstock for biogas production, has been an active area of research. However, lignocellulose poses a lot of operational difficulties- widespread variation in the structural organization of lignocellulosic matrix, amenability to degradation, low bulk density, to name a few. Amongst these, the low bulk density of the lignocellulosic feedstock is crucial to the process operation and optimization. Low bulk densities render the feedstock floating in conventional liquid/wet digesters. Low bulk densities also restrict the maximum achievable organic loading rate in the reactor, decreasing the power density of the reactor. However, during digestion, lignocellulose undergoes very high compaction (up to 26 times feeding density). This first reduces the achievable OLR (because of low feeding density) and compaction during digestion, then renders the reactor space underutilized and also imposes significant mass transfer limitations. The objective of this paper was to understand the effects of compacting lignocellulose on mass transfer and the influence of loss of different components on the bulk density and hence structural integrity of the digesting lignocellulosic feedstock. 10 different lignocellulosic feedstocks (monocots and dicots) were digested anaerobically in a fed-batch, leach bed reactor -solid-state stratified bed reactor (SSBR). Percolation rates of the recycled bio-digester liquid (BDL) were also measured during the reactor run period to understand the implication of compaction on mass transfer. After 95 ds, in a destructive sampling, lignocellulosic feedstocks digested at different SRT were investigated to quantitate the weekly changes in bulk density and lignocellulosic composition. Further, percolation rate data was also compared to bulk density data. Results from the study indicate loss of hemicellulose (r²=0.76), hot water extractives (r²=0.68), and oxalate extractives (r²=0.64) had dominant influence on changing the structural integrity of the studied lignocellulose during anaerobic digestion. Further, feeding bulk density of the lignocellulose can be maintained between 300-400kg/m³ to achieve higher OLR, and bulk density of 440-500kg/m³ incurs significant mass transfer limitation for high compacting beds of dicots.

Keywords: anaerobic digestion, bulk density, feed compaction, lignocellulose, lignocellulosic matrix, cellulose, hemicellulose, lignin, extractives, mass transfer

Procedia PDF Downloads 161
2125 Early-Age Mechanical and Thermal Performance of GGBS Concrete

Authors: Kangkang Tang

Abstract:

A large amount of blast furnace slag is generated in China. Most ground granulated blast furnace slag (GGBS) however ends up in low-grade applications. Blast furnace slag, ground to an appropriate fineness, can be used as a partial replacement of cementitious material in concrete. The potential for using GGBS in structural concrete, e.g. concrete beams and columns, is investigated at Xi’an Jiaotong-Liverpool University (XJTLU). With 50% of CEM I replaced with GGBS, peak hydration temperatures determined in a suspended concrete slab reduced by 20%. This beneficiary effect has not been further improved with 70% of CEM I replaced with GGBS. Partial replacement of CEM I with GGBS also has a retardation effect on the early-age strength of concrete. More GGBS concrete mixes will be conducted to identify an ‘optimum’ replacement level which will lead to a reduced thermal loading, without significantly compromising the early-age strength of concrete.

Keywords: thermal effect, GGBS, concrete strength and testing, sustainability

Procedia PDF Downloads 402
2124 Prevalence of Gastro-Intestinal Helminthes of Farm Animals by Coprological Examination

Authors: Mohammad Saleh Al-Aboody

Abstract:

In the present study 442 fecal samples from cattle, buffaloes, and sheep for contamination with helminthes. Samples were examined from 171 cattle, 128 buffaloes, and 143 sheep. The testing, during the period from May 2014 to April 2015, showed that 81 out of 171cattle were positive for helminthes infection (47.3%), with the rate of infection higher in females (55%) than in males (40%). In buffaloes, 41 of 128 tested were positive, a 32% rate of infection. Again, the infection rate was higher in females (47%) than in males (22%). In sheep, the rate of infection was highest of all three species. The results showed that, the infection rate among cattle were 50.3 % and Trichostrongyle species were the predominant parasites among both cattle and buffaloes. The prevalence rate was much higher in females than males. Regarding seasonal dynamics the highest infection rates with helminthes reported was in spring season.

Keywords: helminthes, prevalence, ruminants, trichostrongyle

Procedia PDF Downloads 367
2123 Students' Statistical Reasoning and Attitudes towards Statistics in Blended Learning, E-Learning and On-Campus Learning

Authors: Petros Roussos

Abstract:

The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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2122 The Best Methods of Motivating and Encouraging the Students to Study: A Case Study

Authors: Mahmoud I. Syam, Osama K. El-Hafy

Abstract:

With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

Procedia PDF Downloads 467