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New Leading-Edge Reinforcement Design of Aircraft Wing to Withstand Bird Collision
(2026-05-01)
Ngamlikitlert, Suppasin
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Kim, Minsung
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Sleesongsom, Suwin
Bird strikes are a key threat to aircraft wing leading edges. This investigation evaluates a honeycomb block reinforcement concept to improve bird strike resistance while maintaining structural efficiency. A validated simulation was developed using an explicit dynamic finite element approach, in which the bird was modeled as a soft body using smoothed particle hydrodynamics, and the wing leading edge was represented with a honeycomb block reinforcement concept. A design of experiments based on McKay Latin hypercube sampling was applied to comprehensively examine the effects of the geometric parameters on the maximum von Mises stress and maximum deformation. Response surface regression models were then constructed to approximate the impact responses and analyze the model correctness. These models were subsequently integrated into a constrained optimization methodology using sequential quadratic programming and population-based integrated learning to minimize deformation while limiting stress below the material yield threshold. The optimized honeycomb and skin configuration demonstrated a noticeable optimization of the maximum deformation within the yield stress limit compared with the baseline design. The results confirm that the proposed honeycomb block reinforcement concept, combined with a regression-based optimization strategy, constitutes a practical, computationally effective approach to improving bird strike resistance and provides a feasible design option for future impact-resistant wing leading-edge designs.
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Four-Bar Linkage Path Generation Problems Using a New TLBO and Optimum Path Repairing Technique
(2026-03-01)
Winyangkul, Seksan
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Alfouneh, Mahmoud
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Sleesongsom, Suwin
A self-adaptive variant of teaching–learning-based optimization, incorporating a diversity archive and referred to as ATLBO-DA, has been proposed. Combined with a new path repairing technique (PRT), it efficiently accomplishes the four-bar linkage path generation problem, but an upgraded version is needed. An update of ATLBO-DA to self-adaptive teaching–learning-based optimization with evenness factor archive (ATLBO-EFA) and a new path repairing technique are proposed at the present. The diversity archive idea of the original version is replaced with the evenness factor archive to increase the exploitation and exploration performance of the TLBO. An optimum path repairing technique (OPRT) is proposed. This novel approach is used to identify the optimum combination of four-bar mechanism types by employing the concept of Degree of Limiting (DL). Moreover, in this article, a comparative analysis of present update and the previous version use to solve four-bar linkage path generation problems is performed. Several path generation problems are solved using both techniques. The results demonstrate that the updated technique consistently outperforms the earlier version, giving superior values for both mean and minimum descriptive statistics. In addition, the results make it clear that ATLBO-EFA and OPRT are superior to the original version. The result of non-parametric statistic testing using Friedman test indicate that ATLBO-EFA ranks 1st at p-value (0.0455) < α (0.05). It can be concluded that ATLBO-EFA with OPRT offers the best solution for solving the four-bar path synthesis problems.
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MODELING AND OPTIMIZATION OF SACCHARIFICATION AND FERMENTATION OF BROKEN RICE
(2026-01-01)
Thuy, Nguyen Minh
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Hung, Tran Huy
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Viet Ha, Lam Thi
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Van Hao, Hong
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Giau, Tran Ngoc
Rice wine is a traditional alcoholic beverage derived from fermented glutinous rice or broken rice. The method is separated into two steps: first, the rice is cooked and liquefied/saccharified by molds and enzymes, followed by fermentation. The study examined how Aspergillus oryzae (0.1 - 0.2%) and α-amylase (0.01 - 0.04%) affect starch liquefaction and saccharification, as well as how Saccharomyces bayanus concentration (0.02 - 0.05%) and total soluble solids content (22 - 26%) impact rice wine fermentation. To improve process prediction and optimization, an artificial neural network integrated with a genetic algorithm (ANN-GA) was applied to model the nonlinear relationships between process variables and fermentation performance. The optimization approach utilizing a machine learning-based model demonstrated better prediction ability. Compared with conventional regression approaches, the ANN-GA model provided improved predictive accuracy and enabled the identification of optimal processing conditions for both saccharification and fermentation stages. The optimum content of Aspergillus oryzae and α-amylase was 0.181% and 0.036%, respectively, resulting in high starch saccharification efficiency with a total soluble solids content of 27.2oBrix. The volume of sugar solution achieved was 34.01 mL (from 50 g rice, yield 68.02%). In addition, using the optimal content of Saccharomyces bayanus of 0.043% and fermenting in an environment with high soluble solids content of 24.88oBrix produced wine with high ethanol and ester content, 12.19% by volume and 0.93 g/L, respectively. The methanol content of the fermented product under these optimal conditions was lower (49.8 mg/L). These findings demonstrate that the integration of machine-learning-based optimization can effectively enhance fermentation efficiency while maintaining product safety. Overall, the optimized saccharification and fermentation parameters provide a viable approach for producing rice wine with higher quality and safety assurances for this traditional product.
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ENHANCING SUGAR RECOVERY FROM SUGARCANE BAGASSE: OPTIMIZING MICROWAVE-ASSISTED ALKALINE PRETREATMENT METHODS FOR BIOBASED ENERGY
(2025-01-01)
Kingkaew, Engkarat
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Tanasupawat, Somboon
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Phuengjayaem, Sukanya
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Poothong, Saranporn
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Ochaikul, Duangjai
This study optimized microwave-assisted alkaline pretreatment for enhancing sugar recovery from sugarcane bagasse. Bagasse was dried, ground, and sieved to a uniform particle size before undergoing pretreatment with sodium hydroxide (NaOH). The effects of microwave power, duration, and NaOH concentration were investigated. Optimal conditions were identified as 800 W microwave power, 8% (w/v) NaOH, and a 2-minute duration (18.69 ± 0.05 g/L). An NaOH concentration of 8% (w/v) achieved high sugar recovery while minimizing chemical use, highlighting the balance between efficiency and sustainability. These findings provide a foundation for improving lignocellulosic biomass pretreatment for biofuel and biochemical production.
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Convergence property of Nesterov-accelerated adaptive moment estimation with safety helmet detection and classification in smart industry application
(2024-11-15)
Jirakitpuwapat, Wachirapong
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Dubey, Premnath
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Prasertsuk, Narachata
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Phanthong, Chaowarit
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Tritham, Chatchai
We propose a technique for first-order gradient-based optimization of stochastic objective functions called Nesterov-accelerated adaptive moment assessment, which makes use of dynamic evaluations of lower-order moments. The adaptive moment assessment and the Nesterov acceleration gradient are combined. Consequently, it has perks, and this technique is convenient to use, numerically economical, memory-light, and very well-suited for challenges with massive amounts of information and characteristics. Additionally, we investigate the algorithm's convergence characteristics and propose a conservative constraint on the convergence rate. Finally, we employ this technique for the detection and classification of safety helmets.
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Hybrid Ant Colony Optimization Method for the Traveling Salesman Problem
(2024-01-01)
Janjarassuk, Udom
The traveling salesman problem (TSP) is a classic problem in computer science and operations research which involves finding the shortest possible route that visits a given set of cities. In this paper, we propose a hybrid algorithm for solving such problem. The algorithm combines the ant colony optimization (ACO) method with the 2-opt heuristic to improve the efficiency for solving the TSP. Instances from the TSPLIB were used to test the algorithm. The results showed that the hybrid ACO algorithm was more effective in solving the TSP as compared to the traditional ACO or the 2-opt heuristic methods.
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Cache Node Placement Scheme Considering Maximum Traffic in Content-Centric Networks
(2023-01-01)
Pavarangkoon, Praphan
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Nakajima, Shohei
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Kitsuwan, Nattapong
This paper proposes a cache node placement scheme considering the maximum traffic in content-centric networks (CCNs). The cache node placement problem is considered to satisfy the user's requirement in CCNs. Traffic utilization is one of the most common requirements. Reduced traffic allows more additional traffic on links. In this paper, a scheme to minimize the maximum traffic and the number of hops is proposed. The mathematical model for the cache node placement problem is formulated. The dynamic routing is considered in this model. Numerical result shows that the proposed scheme outperforms the conventional scheme. It suggests that the proposed scheme provides reference values to support the implementation of heuristic algorithms for the cache node placement problem.
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Process of foam-mat drying of purple rice bran extract and evaluation of product properties
(2023-01-01)
Loan, L. T.K.
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Tai, N. V.
The present study examined the process of foam-mat drying “Cám” purple rice bran extract, including optimization foaming conditions and effect of drying temperatures on the drying behaviours and powder's qualities. The egg album and xanthan gum at different levels were used as foaming agents, which further optimizied by the response surface methodology. The optmial foam was dried at four levels of temperature (50-80oC). Moisture content was further recorded every 30 minutes. Four common emperical models were applied for predicting the pattern of moisture content. Under the effect of heat treatment, the final qualities of Cám purple rice bran foam-mat dried powder were determined. The results showed that when egg albumin and xanthan gum were used, 12.04% and 0.337% could maximize foam expansion and stability. These conditions could facilitate the efficiency of the drying process. Moreover, among the four models, the Page model showed the best fit for predicting the change in moisture ratio. The effective diffusivity and activation energy were from 6.73 x 10-10 to 1.66 x 10-9 m2/s and 22.72 kJ/mol, respectively. The study also revaled that at temperature of 70oC, the product could maintain high antioxidant proper conditions for storage and high acceptance by consumer.
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Optimizing Distribution Network Models for a Fruit Trading Company in Thailand: A Comparative Study Using Linear Programming and Optimization
(2023-01-01)
Akkawuttiwanich, P.
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Yenradee, P.
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Horng, S.
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Pichpibul, T.
This research investigates the distribution network model of a fruit trading company in Thailand, with a specific focus on the problem of excessive travel distances and vehicle requirements in the company's existing distribution system. Linear programming and optimization techniques are used to improve the distribution network model and to satisfy the daily demand. Results are compared between the current distribution scenario and the optimized model. The computational analysis reveals a significant 21.8% reduction (802 kilometers) in total traveling distance and a 33.33% decrease in the number of vehicles required. Additionally, a comprehensive cost analysis is proposed, incorporating fuel costs, CO2 emissions, and overtime expenses, which were previously overlooked. This research offers valuable insights into the potential benefits of optimization, including cost savings and environmental impact reduction, providing a practical template for managing distribution networks, reducing reliance on ad hoc practices, and fostering a sustainable business model to enhance competitiveness in a challenging market.
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Extraction Optimization of Crocin from Gardenia (Gardenia jasminoides Ellis)Fruits Using Response Surface Methodology and Quality Evaluation of Foam-Mat Dried Powder
(2022-12-01)
Thuy, Nguyen Minh
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Nhu, Pham Huynh
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Tai, Ngo Van
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Minh, Vo Quang
The crocin in gardenia, as a medical plant, has drawnthe attention of researchers and scientists due to its color and high antioxidant activity. To optimize the extraction parameters of crocin from gardenia fruits, response surface methodology (RSM) was employed.The effects of four independent variables, namely extraction temperature (45–55 °C), time (40–60 min), percentage of gardenia fruits(15–25%), and ethanol concentration (50–60%),on a crocin compound were investigated. The extract from the gardenia fruit was dried at different temperatures (55–70 °C) by the foam-mat drying method. The optimal extraction parameters were an extraction temperature of 55 °C, time of 57 min, percent of fruits in solvent at 24%, and an ethanol concentration of 56%. The results showed that the dried gardenia powder had maintained the crocin content well(6.64 mg/g), and the product with low water activity and moisture content of 0.33 and 5.72%, respectively, is suitable for storage. The foam-mat dried product also maintains the natural color and characteristics inherent in the raw materials, which could also be used as supplemental ingredients for other food industries.

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