Search results for: safety validation

Authors: Emad Al-Abdallat, Faris G. Bakri, Azmi Mahafza, Rayyan Al Ali, Nidaa Ababneh, Ahmed Idhair

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Background: Morgues are high-risk areas for the spread of infection from the cadavers to the staff during the postmortem examination. Infection can spread from corpses to workers by the airborne route, by direct contact, or from needle and sharp object injuries. Objective: Knowledge about the prevalence of these infections among autopsies is prudent to appreciate any risk of transmission and to further enforce safety measures. Method: A total of 242 autopsies were tested. Age ranged from 3 days to 94 years (median 75.5 years, mean 45.3 (21.9 ± SD)). There were 172 (71%) males. Results: The cause of death was considered natural in 137 (56.6%) cases, accidental in 89 (36.8%), homicidal in 9 (3.7%), suicidal in 4 (1.7%), and unknown in 3 (1.2%). Hepatitis B surface antigen was positive in 5 (2.1%) cases. Hepatitis C virus antibody was detected in 5 (2.1%) cases and the hepatitis C virus polymerase chain reaction was positive in 2 of them (0.8%). HIV antibody was not detected in any of the cases. Conclusions: Autopsies can be associated with exposure to blood borne viruses. Autopsies performed during the study period were tested for hepatitis B surface antigen, hepatitis C virus antibody, and human immunodeficiency virus antibody. Positive tests were subsequently confirmed by polymerase chain reaction. There is low prevalence of infections with these viruses in our autopsy cases. However, the risk of transmission remains a threat. Healthcare workers in the forensic departments should adhere to standard precautions.

Keywords: autopsy, hepatitis B virus, hepatitis C virus, human immunodeficiency virus, Jordan

Procedia PDF Downloads 368

Authors: Lin Zhao, Hanqiao Jiang, Junjian Li

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Polymers injected into elevated-temperature reservoirs inevitably suffer from thermal degradation, resulting in severe viscosity loss and poor flooding performance. However, for polymer flooding in such reservoirs, present simulators fail to provide accurate results for lack of description on thermal degradation. In light of this, the objectives of this paper are to provide a simulation model for polymer flooding with thermal degradation and study the effect of thermal degradation on polymer flooding in elevated-temperature reservoirs. Firstly, a thermal degradation experiment was conducted to obtain the degradation law of polymer concentration and viscosity. Different types of polymers degraded in the Thermo tank with elevated temperatures. Afterward, based on the obtained law, a streamline-assistant model was proposed to simulate the degradation process under in-situ flow conditions. Model validation was performed with field data from a well group of an offshore oilfield. Finally, the effect of thermal degradation on polymer flooding was studied using the proposed model. Experimental results showed that the polymer concentration remained unchanged, while the viscosity degraded exponentially with time after degradation. The polymer viscosity was functionally dependent on the polymer degradation time (PDT), which represented the elapsed time started from the polymer particle injection. Tracing the real flow path of polymer particle was required. Therefore, the presented simulation model was streamline-assistant. Equation of PDT vs. time of flight (TOF) along streamline was built by the law of polymer particle transport. Based on the field polymer sample and dynamic data, the new model proved its accuracy. Study of degradation effect on polymer flooding indicated: (1) the viscosity loss increased with TOF exponentially in the main body of polymer-slug and remained constant in the slug front; (2) the responding time of polymer flooding was delayed, but the effective time was prolonged; (3) the breakthrough of subsequent water was eased; (4) the capacity of polymer adjusting injection profile was diminished; (5) the incremental recovery was reduced significantly. In general, the effect of thermal degradation on polymer flooding performance was rather negative. This paper provides a more comprehensive insight into polymer thermal degradation in both the physical process and field application. The proposed simulation model offers an effective means for simulating the polymer flooding process with thermal degradation. The negative effect of thermal degradation suggests that the polymer thermal stability should be given full consideration when designing polymer flooding project in elevated-temperature reservoirs.

Keywords: polymer flooding, elevated-temperature reservoir, thermal degradation, numerical simulation

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Authors: Gholamhassan Kakha, Mohsen Jami, Daniel Alex Merino Natorce

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Sustainable development refers to the creation of a balance between the development and the environment too; it consists of three key principles namely environment, society and economy. These three parameters are related to each other and the imbalance occurs in each will lead to the disparity of the other parts. Mining is one of the most important tools of the economic growth and social welfare in many countries. Meanwhile, assessment of the environmental impacts has directed to the attention of planners toward the natural environment of the areas surrounded by mines and allowing for monitoring and controlling of the current situation by the designers. In this look upon, a semi-quantitative model using a matrix method is presented for assessing the environmental impacts in the BOOG Granite Mine located in Sistan and Balouchestan, one of the provinces of Iran for determining the effective factors and environmental components. For accomplishing this purpose, the initial data are collected by the experts at the next stage; the effect of the factors affects each environmental component is determined by specifying the qualitative viewpoints. Based on the results, factors including air quality, ecology, human health and safety along with the environmental damages resulted from mining activities in that area. Finally, the results gained from the assessment of the environmental impact are used to evaluate the sustainability by using Philips mathematical model. The results show that the sustainability of this area is weak, so environmental preventive measures are recommended to reduce the environmental damages to its components.

Keywords: sustainable development, environmental impacts' assessment, BOOG granite, Philips mathematical model

Procedia PDF Downloads 190

Authors: Kelvin Lo

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Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

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Authors: Pranab Kumar Goswami

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According to WHO, over 1000 million people worldwide are employed in small-scale industries. The ‘garment’ industry’ is one such industry in developing countries. These garment SMEs are mostly run by private establishments in the unorganized sector to avoid legal obligations of OSH provisions. The OSH standards are very poor and even basic health and safety provisions are not provided in such units. The study has been conducted in India among workers employed in the ‘garment’ industry with the objectives to analyze the types and extent of occupational health hazards of the garment workers and to assess the relationship of sociodemographic and occupational factors with various health hazards. The survey method, the tabular method followed by applying simple statistical technique, has been taken into account to analyze the data collected from three SME garment industries in Delhi (India-Asia). The study was conducted in Delhi from August-2019 to October-2020. A random sampling of 70 workers from three factories has been chosen for this study. The study shows that most of the workers were males (82%) and were in the 18-50 age group (78%), with none below 18 years of age. It was found that 26% of the workers were illiterate and most of them belonged to poor socioeconomic status. The study revealed that the nature of the hazards in garment industries in India is mostly physical and mechanical. We found that musculoskeletal problems (54%) were the commonest health problem. The body areas commonly affected were neck, low back, hand, wrist, finger, and shoulder. If garment workers’ health is affected by occupational hazards, it will impact on national health and economic growth of developing countries. Health is a joint responsibility of both government and employing authority.

Keywords: garment, MSD, health hazard, social factor

Procedia PDF Downloads 181

Authors: Naohiro Nakamura

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Analysis methods to accurately estimate the behavior of buildings when earthquakes occur is very important for improving the seismic safety of such buildings. Recently, the use of damping devices has increased significantly and there is a particular need to appropriately evaluate the behavior of buildings with such devices during earthquakes in the design stage. At present, however, the accuracy of the analysis evaluations is not sufficient. One reason is that the accuracy of current analysis methods has not been appropriately verified because there is very limited data on the behavior of actual buildings during earthquakes. Many types of shaking table test of large structures are performed at the '3-Dimensional Full-Scale Earthquake Testing Facility' (nicknamed 'E-Defense') operated by the National Research Institute of Earth Science and Disaster Prevention (NIED). In this study, simulations using 3- dimensional analysis models were conducted on shaking table test of a 5-story steel-frame structure with dampers. The results of the analysis correspond favorably to the test results announced afterward by the committee. However, the suitability of the parameters and models used in the analysis and the influence they had on the responses remain unclear. Hence, we conducted additional analysis and studies on these models and parameters. In this paper, outlines of the test are shown and the utilized analysis model is explained. Next, the analysis results are compared with the test results. Then, the additional analyses, concerning with the hysteresis curve of the dampers and the beam-end stiffness of the frame, are investigated.

Keywords: three-dimensional analysis, E-defense, full-scale experimen, vibration control damper

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Authors: Vanitha Varadharaj, Vijalakshmi Krishnamurthy

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Annona squamosa Linn, commonly known as Sugar apple, belonging to the family Annonaceae, is said to show varied medicinal effects, including insecticide, antiovulatory and abortifacient. The alkaloid and flavonoids present in Annona squamosa leaf has proved to have antioxidant activity. The present work has been planned to investigate the effect of ethanolic leaf extract of Annona squamosa leaf on Den Induced wistar albino rats. The study was carried out to analyze the biochemical Parmeters like Total Proteins, Bilirubin, Enzymatic and Non –Enzymatic enzymes, Marker enzymes and Tumor markers in serum and also the histopathological studies in liver is carried out in control and DEN induced rats. Supplementation of ELAS (Ethanolic Leaf Extract Of Annona squamosa) reduced the liver weight and also reduced the tumour incidence. Chemoprevention group showed near normal values of bilirubin when compared with the control rats. Total protein was decreased in the cancer bearing group and on treatment with the extract the levels of protein were restored. Both in pre and post treatment group, the activities of enzymatic antioxidants such as superoxide dismutase, catalase, and Glutathione peroxidase were increased but in pre treated animals it was more effective than post treated animals. The non- enzymatic antioxidants such as vitamin C and vitamin E were brought back to normal level significantly in post and pre treated animals. Activities of marker enzymes such as SGOT, SGPT, ALP, γ GT were significantly elevated in the serum of cancer animals and the values returned to normal after treatment with the extract suggesting the hepato protective effect of the extract. Lipid peroxide was found to be elevated in the cancer induced group. This condition was brought back to the normal in the pre and post treated animals with ELAS. Histological examination also confirmed the anti- carcinogenic potential of ELAS, Cancer induced groups had a triple fold increase in their AFP values when compared to other groups. DEN treatment increased the level of AFP expression while ELAS partially counteracted the effect of it. So the scientific validation obtained from this study may pave way to many budding scientists to find new drugs from Annona squamosa for various ailments.

Keywords: annona squamosa, biochemical parmeters, cancer, leaf extract

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Authors: Riyadh Jamegh, AllaEldin Kassam, Sawsan Sabih

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In modern trends of market, organizations face high-pressure environment which is characterized by globalization, high competition, and customer orientation, so it is very crucial to control and know the weak and strong points of the supply chain in order to improve their performance. So the performance measurements presented as an important tool of supply chain management because it's enabled the organizations to control, understand, and improve their efficiency. This paper aims to identify supply chain performance measurement (SCPM) by using Fuzzy Analytical Hierarchical Process (FAHP). In our real application, the performance of organizations estimated based on four parameters these are cost parameter indicator of cost (CPI), inventory turnover parameter indicator of (INPI), raw material parameter (RMPI), and safety stock level parameter indicator (SSPI), these indicators vary in impact on performance depending upon policies and strategies of organization. In this research (FAHP) technique has been used to identify the importance of such parameters, and then first fuzzy inference (FIR1) is applied to identify performance indicator of each factor depending on the importance of the factor and its value. Then, the second fuzzy inference (FIR2) also applied to integrate the effect of these indicators and identify (SCPM) which represent the required output. The developed approach provides an effective tool for evaluation of supply chain performance measurement.

Keywords: fuzzy performance measurements, supply chain, fuzzy logic, key performance indicator

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Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

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The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC

Procedia PDF Downloads 297

Authors: Basanta Raj Adhikari

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Large and small scale earthquakes are frequent in the Nepal, Himalaya, and many co-seismic landslides are resulted out of it. Recently, Gorkha earthquake-2015 has triggered many co-seismic landslides destroying many lives and properties. People have displaced their original places due to having many cracks and unstable ground. Therefore, Nepal has been adopting a pronged development strategy to address the earthquake issues through reconstruction and rehabilitation policy, plans and budgets. Landslides are major threat for the mountain livelihood, and it is very important to investigate and mitigate to improve human wellbeing factoring in considerations of economic growth, environmental safety, and sustainable development. Community based landslide investigation was carried with the involvement of the local community in the Sindhupalchowk District of Central Nepal. Landslide training and field orientation were the major methodological approach of this study. Combination of indigenous and modern scientific knowledge has created unique working environment which enhanced the local capacity and trained people for replication. Local topography of the landslide was created with the help of Total Station and bill of quantity was derived based on it. River training works, plantation of trees and grasses, support structures, surface and sub-surface drainage management are the recommended mitigative measures. This is a very unique example of how academia and local community can work together for sustainable development by reducing disaster risk at the local level with very low-cost technology.

Keywords: community, earthquake, landslides, Nepal

Procedia PDF Downloads 147

Authors: T. R. Hidayat, G. Irawan, F. Kurniawan, E. H. I. Prasetya, Suharto, T. F. Ridwan, A. Pitoyo, A. Juniantoro, R. T. Hidayat

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Swab activities is an activity to lift fluid from inside the well with the use of a sand line that aims to find out fluid influx after conducting perforation or to reduce the level of fluid as an effort to get the difference between formation pressure with hydrostatic pressure in the well for underbalanced perforation. During the swab activity, problems occur frequent problems occur with the rubber swab. The rubber swab often breaks and becomes a fish inside the well. This rubber swab fishing activity caused the rig operation takes longer, the swab result data becomes too late and create potential losses of well operation for the company. The average time needed for fishing the fractions of rubber swab plus swab work is 42 hours. Innovation made for such problems is to modify the rubber swab tool. The rubber swab tool is modified by provided a series of brushes at the end part of the tool with a thread of connection in order to improve work safety, so when the rubber swab breaks, the broken swab will be lifted by the brush underneath; therefore, it reduces the loss time for rubber swab fishing. This tool has been applied, it and is proven that with this rubber swab tool modification, the rig operation becomes more efficient because it does not carry out the rubber swab fishing activity. The fish fractions of the rubber swab are lifted up to the surface. Therefore, it saves the fuel cost, and well production potentials are obtained. The average time to do swab work after the application of this modified tool is 8 hours.

Keywords: rubber swab, modifikasi swab, brush, fishing rubber swab, saving cost

Procedia PDF Downloads 159

Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

Procedia PDF Downloads 108

Authors: M. A. Okezue, K. L. Clase, S. R. Byrn

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The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO₄) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO₄ tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO₄ tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.

Keywords: data integrity, spreadsheets, titrimetry, validation, zinc sulphate tablets

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Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

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The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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Authors: Abdalaziz M. Alsalhabi, Loai M. Alowa

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This paper investigates Weld Rejection Rate (WRR) limits and tracer effects in construction projects, with a specific focus on a Gas Plant Project, a mega-project held by Saudi Aramco (SA) in Saudi Arabia. The study included a comprehensive examination of various factors impacting WRR limits. It commenced by comparing the Company practices with ASME standards, followed by an in-depth analysis of both weekly and cumulative projects' historical WRR data, evaluation of Radiographic Testing (RT) reports for rejected welds, and proposal of mitigation methods to eliminate future rejections. Additionally, the study revealed the causes of fluctuation in WRR data and benchmarked with the industry practices. Furthermore, a case study was conducted to explore the impact of tracers on WRR, providing insights into their influence on the welding process. This paper aims to achieve three primary objectives. Firstly, it seeks to validate the existing practices of WRR limits and advocate for their inclusion within relevant International Industry Standards. Secondly, it aims to validate the effectiveness of the WRR formula that incorporates tracer effects, ensuring its reliability in assessing weld quality. Lastly, this study aims to identify opportunities for process improvement in WRR control, with the ultimate goal of enhancing project processes and ensuring the integrity, safety, and efficiency of constructed assets.

Keywords: weld rejection rate, weld repair rate in joint and linear basis, tracers effects, construction projects

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Authors: G. R. Khan, Sadia Mahjabin, A. S. Mollah, M. R. Mawla

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Atmospheric dispersion modeling is significant for any nuclear facilities in the country to predict the impact of radiological doses on environment as well as human health. That is why to ensure safety of workers and population at plant site; Atmospheric dispersion modeling and radiation dose calculations were carried out for a hypothetical accidental release of airborne radionuclide from the 3 MW TRIGA research reactor of Savar, Bangladesh. It is designed with reactor core which consists of 100 fuel elements(1.82245 cm in diameter and 38.1 cm in length), arranged in an annular corefor steady-state and square wave power level of 3 MW (thermal) and for pulsing with maximum power level of 860MWth.The fuel is in the form of a uniform mixture of 20% uranium and 80% zirconium hydride. Total effective doses (TEDs) to the public at various downwind distances were evaluated with a health physics computer code “HotSpot” developed by Lawrence Livermore National Laboratory, USA. The doses were estimated at different Pasquill stability classes (categories A-F) with site-specific averaged meteorological conditions. The meteorological data, such as, average wind speed, frequency distribution of wind direction, etc. have also been analyzed based on the data collected near the reactor site. The results of effective doses obtained remain within the recommended maximum effective dose.

Keywords: accidental release, dispersion modeling, total effective dose, TRIGA

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Authors: Mojtaba Zabihi, Stephen Munro, Jonathan Little, Ri Li, Joshua Brinkerhoff, Sina Kheirkhah

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Occupational Safety and Health Administration (OSHA) identified dental workers at the highest risk of contracting COVID-19. This is because aerosol-generating procedures (AGP) during dental practices generate aerosols ( < 5µm) and droplets. These particles travel at varying speeds, in varying directions, and for varying durations. If these particles bear infectious viruses, their spreading causes airborne transmission of the virus in the dental room, exposing dentists, hygienists, dental assistants, and even other dental clinic clients to the infection risk. Computational fluid dynamics (CFD) simulation of two-phase flows based on a discrete phase model (DPM) is carried out to study the spreading of aerosol and droplets in a dental room. The simulation includes momentum, heat, and mass transfers between the particles and the airflow. Two simulations are conducted and compared. One simulation focuses on the effects of room ventilation in winter and summer on the particles' travel. The other simulation focuses on the control of aerosol and droplets' spreading. A suction collector is added near the source of aerosol and droplets, creating a flow sink in order to remove the particles. The effects of the suction flow on the aerosol and droplet travel are studied. The suction flow can remove aerosols and also reduce the spreading of droplets.

Keywords: aerosols, computational fluid dynamics, COVID-19, dental, discrete phase model, droplets, two-phase flow

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Authors: Siti Khadijah Che Osmi, Mohammed Ahmad Syed

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Underground structures are crucial components which required detailed analysis and design. Tunnels, for instance, are massively constructed as transportation infrastructures and utilities network especially in urban environments. Considering their prime importance to the economy and public safety that cannot be compromised, thus any instability to these tunnels will be highly detrimental to their performance. Recent experience suggests that tunnels become vulnerable during earthquakes and blast scenarios. However, a very limited amount of studies has been carried out to study and understanding the dynamic response and performance of underground tunnels under those unpredictable extreme hazards. In view of the importance of enhancing the resilience of these structures, the overall aims of the study are to evaluate probabilistic future performance of shallow tunnels subjected to seismic and blast loads by developing detailed fragility analysis. Critical non-linear time history numerical analyses using sophisticated finite element software Midas GTS NX have been presented about the current methods of analysis, taking into consideration of structural typology, ground motion and explosive characteristics, effect of soil conditions and other associated uncertainties on the tunnel integrity which may ultimately lead to the catastrophic failure of the structures. The proposed fragility curves for both extreme loadings are discussed and compared which provide significant information the performance of the tunnel under extreme hazards which may beneficial for future risk assessment and loss estimation.

Keywords: fragility analysis, seismic loads, shallow tunnels, blast loads

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Authors: Sara Torabi, Sadegh Khazalpour, Mahdi Jamshidi

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Nitro aromatic compounds are valuable materials because of their applications in the preparation of chemical intermediates for the synthesis of dyes, plastics, perfumes, energetic materials, and pharmaceuticals. Chemical and electrochemical procedures are reported for nitration of aromatic compounds. Flavonoid derivatives are present in many vegetables and fruits and are constituent of many common pharmaceuticals and dietary supplements. Electrochemistry provides very versatile means for the electrosynthesis, mechanistic and kinetic studies. To the best of our knowledge, and despite the importance of these compounds in numerous scientific fields, there are no reports on the electrochemical nitration of Quercetin derivatives. Herein, we describe a green electrochemical synthesis of a nitro compound. In this work, electrochemical oxidation of Quercetin has been studied in the presence of nitrite ion as a nucleophile in acetate buffer solution (c = 0.2 M, pH = 6.0), by means of cyclic voltammetry and controlled-potential coulometry. The results indicate the participation of produced o-benzoquinones in Michael reaction with nitrite ion (in the divided cell) to form the corresponding nitro diol (EC mechanism). The purity of product and characterization was done using ¹H NMR, ¹³C NMR, FTIR spectroscopic techniques. The presented strategies use a water/ethanol mixture as solvent. Ethanol as cosolvent was also used in the previous studies because of its low cost, safety, easy availability, recyclability, bioproductability, and biodegradability. These strategies represent a one-pot and facile process for the synthesis of nitro compound in high yield and purity under green conditions.

Keywords: electrochemical synthesis, green chemistry, cyclic voltammetry, molecular docking

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Authors: Alexander Hendricks, Sean Nevin, Clayton Wikoff, Melissa Dougherty, Jacob Orlita, Rafiqul Noorani

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Knee orthotics play an important role in aiding in the recovery of those with knee injuries, especially athletes. However, structural knee orthotics is often very expensive, ranging between $300 and $800. The primary reason for this project was to answer the question: can 3D printed orthotics represent a viable and cost-effective alternative to present structural knee orthotics? The primary objective for this research project was to design a knee orthotic for athletes with knee injuries for a low-cost under $100 and evaluate its effectiveness. The initial design for the orthotic was done in SolidWorks, a computer-aided design (CAD) software available at Loyola Marymount University. After this design was completed, finite element analysis (FEA) was utilized to understand how normal stresses placed upon the knee affected the orthotic. The knee orthotic was then adjusted and redesigned to meet a specified factor-of-safety of 3.25 based on the data gathered during FEA and literature sources. Once the FEA was completed and the orthotic was redesigned based from the data gathered, the next step was to move on to 3D-printing the first design of the knee brace. Subsequently, physical therapy movement trials were used to evaluate physical performance. Using the data from these movement trials, the CAD design of the brace was refined to accommodate the design requirements. The final goal of this research means to explore the possibility of replacing high-cost, outsourced knee orthotics with a readily available low-cost alternative.

Keywords: 3D printing, knee orthotics, finite element analysis, design for additive manufacturing

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Authors: Mohammad A. Khasawneh

Abstract:

Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure. The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab. Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.

Keywords: friction, image analysis, polishing, statistical analysis, texture

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Authors: Ergün Şakalar, Şeyma Özçirak Ergün

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Pistachio nuts, the fruits of the pistachio tree (Pistacia vera), are edible tree nuts highly valued for their organoleptic properties. Pistachio nuts used in snack foods, chocolates, baklava, meat products, ice-cream industries and other gourmet products as ingredients. Undeclared pistachios may be present in food products as a consequence of fraudulent substitution. Control of food samples is very important for safety and fraud. Mix of pistachio, peanut (Arachis hypogaea), pea (Pisum sativum L.) used instead of pistachio in food products, because pistachio is a considerably expensive nut. To solve this problem, a sensitive polymerase chain reaction PCR has been developed. A real-time PCR assay for the detection of pea, peanut and pistachio in baklava was designed by using EvaGreen fluorescence dye. Primers were selected from powerful regions for identification of pea, peanut and pistachio. DNA from reference samples and industrial products were successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. Genomes were identified based on their specific melting peaks (Mp) which are 77°C, 85.5°C and 82.5°C for pea, peanut and pistachio, respectively. Homogenized mixtures of raw pistachio, pea and peanut were prepared with the ratio of 0.01%, 0.1%, 1%, 10%, 40% and 70% of pistachio. Quantitative detection limit of assay was 0.1% for pistachio. Also, real-time PCR technique used in this study allowed the qualitative detection of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA in the experimental admixtures. This assay represents a potentially valuable diagnostic method for detection of nut species adulterated with pistachio as well as for highly specific and relatively rapid detection of small amounts of pistachio in food samples.

Keywords: pea, peanut, pistachio, real-time PCR

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Authors: S. Visetpotjanakit, C. Khrautongkieo

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Radiation monitoring in the environment and foodstuffs is one of the main responsibilities of Office of Atoms for Peace (OAP) as the nuclear regulatory body of Thailand. The main goal of the OAP is to assure the safety of the Thai people and environment from any radiological incidents. Various radioanalytical methods have been developed to monitor radiation and radionuclides in the environmental and foodstuff samples. To validate our analytical performance, several proficiency test exercises from the International Atomic Energy Agency (IAEA) have been performed. Here, the results of a proficiency test exercise referred to as the Proficiency Test for Tritium, Cobalt, Strontium and Caesium Isotopes in Seawater 2017 (IAEA-RML-2017-01) are presented. All radionuclides excepting ³H were analysed using various radioanalytical methods, i.e. direct gamma-ray counting for determining ⁶⁰Co, ¹³⁴Cs and ¹³⁷Cs and developed radiochemical techniques for analysing ¹³⁴Cs, ¹³⁷Cs using AMP pre-concentration technique and 90Sr using di-(2-ethylhexyl) phosphoric acid (HDEHP) liquid extraction technique. The analysis results were submitted to IAEA. All results passed IAEA criteria, i.e. accuracy, precision and trueness and obtained ‘Accepted’ statuses. These confirm the data quality from the OAP environmental radiation laboratory to monitor radiation in the environment.

Keywords: international atomic energy agency, proficiency test, radiation monitoring, seawater

Procedia PDF Downloads 164

Authors: Zineb Touati Hamad, Mohamed Ridda Laouar, Issam Bendib

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With the massive development of technology today, the Arabic language has gained a prominent position among the languages most used for writing articles, expressing opinions, and also for citing in many websites, defying its growing sensitivity in terms of structure, language skills, diacritics, writing methods, etc. In the context of the spread of the Arabic language, the Holy Quran represents the most prevalent Arabic text today in many applications and websites for citation purposes or for the reading and learning rituals. The Quranic verses / surahs are published quickly and without cost, which may cause great concern to ensure the safety of the content from tampering and alteration. To protect the content of texts from distortion, it is necessary to refer to the original database and conduct a comparison process to extract the percentage of distortion. The disadvantage of this method is that it takes time, in addition to the lack of any guarantee on the integrity of the database itself as it belongs to one central party. Blockchain technology today represents the best way to maintain immutable content. Blockchain is a distributed database that stores information in blocks linked to each other through encryption, where the modification of each block can be easily known. To exploit these advantages, we seek in this paper to justify the use of this technique in preserving the integrity of Arabic texts sensitive to change by building a decentralized framework to authenticate and verify the integrity of the digital Quranic verses/surahs spread on websites.

Keywords: arabic text, authentication, blockchain, integrity, quran, verification

Procedia PDF Downloads 149

Authors: Chiang-Lead Woo

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In reply to serious environmental problems, the Taiwan government quickly adjusted some articles to suit the needs of environmental protection recently, such as the amendment to article 190-1 of the Taiwan Criminal Code. The transfer of legislation comes as an improvement which canceled the limitation of ‘endangering public safety’. At the same time, the article 190-1 goes from accumulative concrete offense to abstract crime of danger. Thus, the public looks forward to whether environmental crime following the imposition of fines or penalties works efficiently in anti-pollution by the deterrent effects. However, according to the addition to article 38-2 of the Taiwan Criminal Code, the confiscation system seems controversial legislation to restrain ill-gotten gains. Most prior studies focused on comparisons with the Administrative Penalty Law and the Criminal Code in environmental issue in Taiwan; recently, more and more studies emphasize calculations on ill-gotten gains. Hence, this paper try to examine the deterrent effect in environmental crime by economic analysis of law and environmental economics perspective. This analysis shows that only if there is an extremely high probability (equal to 100 percent) of an environmental crime case being prosecuted criminally by Taiwan Environmental Protection Agency, the deterrent effects will work. Therefore, this paper suggests deliberating the confiscation system from supplementing the System of Environmental and Economic Accounting, reasonable deterrent fines, input management, real-time system for detection of pollution, and whistleblower system, environmental education, and modernization of law.

Keywords: confiscation, ecosystem services, environmental crime, ill-gotten gains, the deterrent effect, the system of environmental and economic accounting

Procedia PDF Downloads 156

Authors: Eiman Kattan, Hong Wei

Abstract:

In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

Procedia PDF Downloads 158

Authors: Mohamed Ziyaina, Ahlam Rajab, Khadija Alkhweldi, Wafia Algami, Omer Al. Toumi, Barbara Rasco1

Abstract:

In recent years, there has been a growing interest in monitoring heavy metal contamination in food products. Spices can improve the taste of food and can also be a source of many bioactive compounds but can unfortunately, also be contaminated with dangerous materials, potentially heavy metals. This study was conducted to investigate lead (Pb) and cadmium (Cd) contamination in selected spices commonly consumed in Libya including Capsicum frutescens (chili pepper) Piper nigrum, (black pepper), Curcuma longa (turmeric), and mixed spices (HRARAT) which consist of a combination of: Alpinia officinarum, Zingiber officinale and Cinnamomum zeylanicum. Spices were analyzed by atomic absorption spectroscopy after digestion with nitric acid/hydrogen peroxide. The highest level of lead (Pb) was found in Curcuma longa and Capsicum frutescens in wholesale markets (1.05 ± 0.01 mg/kg, 0.96 ± 0.06 mg/kg). Cadmium (Cd) levels exceeded FAO/WHO permissible limit. Curcuma longa and Piper nigrum sold in retail markets had a high concentration of Cd (0.36 ± 0.09, 0.35 ± 0.07 mg/kg, respectively) followed by (0.32 ± 0.04 mg/kg) for Capsicum frutescens. Mixed spices purchased from wholesale markets also had high levels of Cd (0.31 ± 0.08 mg/kg). Curcuma longa and Capsicum frutescens may pose a food safety risk due to high levels of lead and cadmium. Cadmium levels exceeded FAO/WHO recommendations (0.2 ppm) for Piper nigrum, Curcuma longa, and mixed spices (HRARAT).

Keywords: heavy metals, lead, cadmium determination, spice

Procedia PDF Downloads 626

Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

Procedia PDF Downloads 257