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Innovative Approaches to RC Deep Beam Strengthening: Evaluating Low-Cost Glass Fiber Wraps Against Traditional CFRP Solutions
(2025-03-01)
Saingam, Panumas
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Ejaz, Ali
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Gadagamma, Chaitanya Krishna
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Hussain, Qudeer
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Sua-iam, Gritsada
This study evaluates the performance of lightweight aggregate deep beams strengthened with low-cost glass fiber-reinforced polymer composite (Lo-G) wraps as an alternative to expensive synthetic fiber-reinforced polymers (FRPs). The investigation includes side-bonded and fully wrapped configurations of Lo-G wraps, alongside carbon FRP (CFRP) strips for comparison. The experimental results show that epoxy-based anchors provided significantly better resistance against de-bonding than mechanical anchors, improving beam performance. Strengthening with Lo-G wraps resulted in a peak capacity increase of 17.0% to 46.9% for side-bonded beams in Group 2, 10.5% to 41.4% for fully wrapped beams in the strip configuration in Group 3, and 15.4% to 42.7% for CFRP strips in Group 4. The ultimate deflection and dissipated energy were also improved, with dissipated energy increases of up to 264.6%, 322.3%, and 222.7% for side-bonded and fully wrapped Lo-G wraps and CFRP strips, respectively. The side-bonded configuration with two or three Lo-G wraps, supplemented by epoxy wraps, outperformed fully wrapped 250 mm strips in peak capacity, with peak capacity improvements of up to 46.9%. However, beams with mechanical anchors showed poor performance due to premature debonding. They rely on friction and expansion within the concrete to resist pull-out forces. If the surrounding concrete is not strong enough or if the anchor is not properly installed, it can lead to failure. Additionally, reducing strip spacing negatively impacted performance. Lo-G wraps showed an 8.5% higher peak capacity and 32.8% greater dissipated energy compared to CFRP strips. Despite these improvements, while Lo-G wraps are a cost-effective alternative, their long-term performance remains to be investigated. None of the existing models accurately predicted the shear strength contribution of Lo-G wraps, as the lower elastic modulus and tensile strength led to high deviations in prediction-to-experimental ratios, underscoring the need for new models to assess shear strength.
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A Kinetic Study on Starch Digestibility and Polyphenol Release of Different Physically Modified Riceberry Flours During In Vitro Stimulated Gastrointestinal Digestion
(2025-01-01)
Van Ngo, Tai
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Naphatrapi, Luangsakul
Riceberry rice has a dark purple color; and a high content of antioxidants, which could affect the digestion behaviors and its application. This study is aimed to analyze the starch digestion rate and predict the bio-accessibility of polyphenols in various modified Riceberry flours during the in vitro digestive process. It also discussed the relationship between the rate of digestion and polyphenol release, which provided basic information about the digestion behavior of Riceberry flour. Seven rice flour samples were used for this study, which included six physically treated flours: annealed flour (AF), heat moisture-treated flour (HMT), pregelatinized flour (Pregel), ultra-sonicated flour (US), wet microwave-treated flour (Wet), dry microwave treated flour (Dry), and untreated (control sample). The obtained results showed that, compared with the control sample, the digestion rate of the Pregel sample was higher, while the others had lower values. However, the Pregel sample showed the second highest rank of bio-accessible polyphenol during digestion after the US sample. While the HMT sample presented the lowest rate of starch digestion and release of bioactive compounds. This investigation also used an artificial neural network (ANN) to forecast the starch digestion and polyphenol bio-accessibility of rice flours. During digestion, the ANN model demonstrated a high capacity to predict the polyphenol bio-accessibility and starch hydrolysis percentage. There was a goodness of fit between the ANN-predicted and the actual values (R2 >0.95). The importance of the bioavailability and bio-accessibility analysis indicates the functional potential that flour can have, which could be predicted effectively by applying modern techniques such as the ANN model. Moreover, it was also concluded that the digestive tract readily absorbs released polyphenol compounds in rice flour, which also influences the rate of starch hydrolysis. However, the impact could vary depending on the flour’s starch fraction content and the polyphenol activity, which is a topic for future investigation. The high antioxidant content and low digestion rate of flour could be highly promising functional materials for application in the food industry..
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Detection of Hardening in Mangosteens Using near-Infrared Hyperspectral Imaging
(2024-04-01)
Workhwa, Saranya
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Khanthong, Thitirat
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Manmak, Napatsorn
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Thompson, Anthony Keith
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Teerachaichayut, Sontisuk
Mangosteens can develop a postharvest physiological disorder, called “hardening”, which affects their marketability and is not detectable using visual inspection. The hardening disorder of mangosteens was determined by firmness value using the texture analyzer. Near-infrared hyperspectral imaging (NIR-HSI) in the region of 935–1720 nm was tested as a possible rapid and non-destructive method to detect this disorder. The spectra from a region of interest of mangosteens were acquired and used for analysis. Calibration models for firmness of a similarly sized group and a mixed-size group were established using partial least squares regression (PLSR) and support vector machine regression (SVMR). Chemometric algorithms were investigated in order to determine the optimal conditions for establishing the models for firmness. The optimum model was obtained when the fruit were graded into similarly sized groups. Using partial least squares regression (PLSR), the correlation coefficient of prediction (R<inf>p</inf>) was 0.87 and the root mean square error of prediction (RMSEP) was 6.25 N. The predictive images for firmness of the fruit were created by interpreting predicted firmness visualized as colors in every pixel. From the data, it was concluded that NIR-HSI can potentially be used to visualize hardening of individual mangosteens based on their predictive images.
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Performance Evaluation of Pre-Processing and Pre-Treatment Algorithm for Near-Infrared Spectroscopy Signals: Case Study pH of Intact Mango “Arumanis”
(2022-08-01)
Agustina, Sri
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Devianti
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Bulan, Ramayanty
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Muslih, Muhamad
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Sitorus, Agustami
pH is one of the important physical parameters to characterize mango damage because it can indicate changes in the structure and chemical content of the fruit. Thus, the present work evaluated the possibility of NIRs as a rapid and non-destructive tool for measuring the pH properties of intact mango from the cultivar "Arumanis" (Mangifera indica L.) using several algorithms for pre-processing, pre-treatment, and prediction. Three different algorithm predictions, namely principal component regression (PCR), partial least squares regression (PLSR), and support vector machine regression (SVMR), were used and compared to predict the pH of mangos. A total of 16 pre-processing and pretreatment algorithms are used to support algorithm prediction, and the results are also compared with the raw data spectra. The NIR spectral data used range from 1000 to 2500 nm. Algorithm performance will be evaluated using RMSE, error differences and concluded using RPD. The results show that the prediction of the PLSR algorithm can be performed with an RPD of 8.17, which is more significant than the PCR and SVMR algorithms, which are 1.04, and 1.90, respectively. To support this, pre-processing and pretreatment of the second derivative Savitzky–Golay is the best algorithm that can be used to predict the pH of the whole mango cultivar "Arumanis".
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Influenza transmission model by dynamical analysis and cellular automata
(2020-09-30)
Pongsumpun, Puntani
The infection of the airways and lung called as influenza. The influenza cases occurred every year. We can find influenza cases around the world. Influenza is an acute respiratory disease. Symptoms of the disease include fever, headache, myalgia, sore throat and cough. Children who infected with influenza may be associated with gastrointestinal symptoms such as nausea, vomiting, and diarrhea. The influenza cases are found in children and adults. SEIR model (S = susceptible, E = exposed, I = infectious, R = recovered) is described for the transmission of influenza. We analyzed the model by using dynamical analysis and Cellular automata is done to see the spread of influenza. The effects of each parameters influence to the transmission of this disease are shown.
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Feasibility of using a photoelectric sensor combined with density measurements for nondestructive assessment of the freshness of Hen's eggs
(2018-11-09)
Teerachaichayut, S.
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Pansiri, J.
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Nguanprasert, P.
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Thepwapee, W.
Quality of hen's eggs relates to their storage time. Freshness of hen's eggs is an important quality but it cannot be determined by a visual inspection, the only way is to take a sample from a batch of eggs and test the sample destructively by the internationally accepted Haugh method. This study used a photoelectric sensor in order to test whether it could be used as a nondestructive test to detect the freshness of hen's eggs when combined with measurement of their density by displacement in water. Eggs were stored at 25°C for up to 20 days and each egg was tested at intervals first with the photoelectric sensor, then their density was measured and finally each egg was broken and subject to the Haugh test. A training set (N=64) was used to establish a model for predicting the freshness of the eggs based on storage time using multiple linear regression. A test set (N=32) was used to test the model. The model had a coefficient of determination (R2) of 0.881 and the root mean square error of prediction (RMSEP) of 2.36 days. This showed that the photoelectric sensor combined with density measurements could be used to develop a model that gave reliable results for nondestructive prediction of the freshness of hen's eggs and how this changed during storage.
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A Model of Engineering Education for Innovation
(2018-09-17)
Sunthonkanokpong, Wisuit
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Murphy, Elizabeth
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Tuntrakool, Sunti
The purpose of this paper is to present implications of innovation for Engineering Education (EE) and research. The specific objectives are as follows: Analyze innovation policies from India, Malaysia, Thailand, Korea and the Association of South-East Nations (ASEAN): Identify common themes between policies; determine implications for EE for Innovation (EEFI); create a model of EEFI; determine implications for EEFI research. Analysis of the policies led to the identification of seven themes: prosperity, humanity, inclusivity, capacity, sustainability, inquiry, and community. These themes guided the creation of a model of EEFI. The model consists of four principal bases: learner-based; STEM + AE-based, problem-based and; project-based. Learner-based focuses on what engineers are in terms of their personal and professional competencies. STEM + AE are a reminder that engineers must be more than technicians, well-versed in STEM. Their education needs to include the arts and entrepreneurship. The problem base refers to EEFI activity being driven by complex, authentic, ill-structured challenges, problems and issues that have a social as well as a technical character. The project-base involves collaborative efforts to find answers to questions and create solutions to problems and challenges. Implications for research highlight a range of approaches to researching EEFI from quantitative surveys of perceptions of participants to complex research designs whereby engineers in training are collaboratively solving real problems in communities.
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Modelling and experimental validation of enantioseparation of racemic phenylalanine via a hollow fibre-supported liquid membrane
(2014-02-01)
Prapasawat, Tatchanok
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Lothongkum, Anchaleeporn Waritswat
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Pancharoen, Ura
This paper reports on the enantioseparation of racemic phenylalanine or D-phenylalanine and Lphenylalanine via a hollow fibre-supported liquid membrane (HFSLM) and the results are compared with the mathematical model. The enantioseparation results, of 80 % and 73 %, showed the highest extraction and stripping of l-phenylalanine from the feed phase and the enantiomeric excess (% ee) of 60 % from 6 mmol L-1 of initial rac-phenylalanine in the feed solution. The optimum parameters were feed solution at pH 5, 6 mmol L L-1 of O,O′-dibenzoyl-(2S,3S)-tartaric acid ((+)-DBTA) as the extractant in octanol as the liquid membrane, and deionised water as the stripping solution. Equal flow-rates of feed and stripping solutions of 100 mL minL-1 were adjusted in a batch operation mode for 50 min at ambient temperature. From the calculation, the equilibrium constants of extraction (K <inf>ex</inf>) and mass transfer coefficients in the feed phase (k <inf>f</inf>) and in the liquid membrane phase (k <inf>m</inf>) were found to be 1.81 L mmol-2, 3.50 × 10-2 cm s-1, and 1.40 × 10-2 cm s-1, respectively. Finally, the change in concentrations of d,l-phenylalanine over time in the feed and stripping solutions by mathematical model were estimated and compared with the experimental results. The values thus calculated were in agreement with the experimental data with the average deviation of approximately 3 %. © 2013 Institute of Chemistry, Slovak Academy of Sciences.

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