Thailand Center of Excellence in Physics

Accurate navigation in outdoor environments requires integrating multiple sensor sources for reliable localization and trajectory tracking. This study proposes Pure Pursuit with Dynamic Steering Control (PP-DSC), which adaptively adjusts both lookahead distance and velocity based on steering angle. The algorithm was deployed on a four-wheeled steering-type autonomous mobile robot (AMR) using Robot Operating System 2 (ROS 2) Jazzy, with real-time sensor fusion from GNSS-RTK, IMU, and wheel encoders. Experiments were conducted on straight, circular, and figure-eight trajectories at 1.0–5.0 m/s in an open area (64 × 20 m). PP-DSC achieved mean lateral deviations of 0.05, 0.07, and 0.08 m respectively, representing 68–82% improvement over standard PP (means 0.19, 0.40, and 0.27 m). To evaluate cross-domain applicability, the algorithm was extended with a Fire and Explosion Index (F&EI)-based safety factor (Safety-integrated PP-DSC) and tested via simulation in an empty fruit bunch (EFB) biodiesel plant (92 × 65 m). Standard PP outperformed Safety-integrated PP-DSC by 15.6% in this industrial setting due to tight turning radii (5–9 m), though Safety-integrated PP-DSC retained advantages in moderate-curvature sections with 11–17% improvement. The F&EI-based safety integration added less than 1% tracking overhead while providing automatic velocity reduction in hazard zones for Process Safety Management (PSM) compliance. The findings confirm that PP-DSC significantly improves trajectory tracking in open-field environments, while industrial deployment requires geometry-specific algorithm selection.

As the popularity and accessibility of artificial intelligence (AI) in learning continue to rise, online education has increasingly incorporated AI. It is imperative to investigate how AI in the scholarly community supports the learning of autonomous students. This scoping review investigated articles that employed AI in discussion forums. The objective of this study is to develop a summary that denotes the effective integration of AI in discussion forums, thereby characterizing the overall learning experience. In accordance with the search, appraisal, synthesis, and analysis (SALSA) framework, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram was employed to design the article screening and selection process. Scopus was utilized for the literature search, resulting in the identification of twelve articles that met the predetermined inclusion and exclusion criteria. The extracted articles covered the following six applications: intelligent tutoring systems, AI-assisted apps, chatbots, automatic formative assessment, AI teaching assistants, and AI-assisted lifelong learning assistants. Three types of man-machine partnerships related to the activities are discussed: student-AI partnerships, student-AI-student partnerships, and student-AI-teacher partnerships, the latter being the most commonly observed. The generated content was frequently processed through teacher adjustments and checks. Components of community of inquiry theory were adapted as indicators. Cognitive presence was observed to be more predominant than social presence, with a particular emphasis on individual learning achievements. Three distinct perspectives regarding the role of AI in learning were identified. The first perspective posited that AI functioned as a virtual teacher, supplementing the teaching functions of human teachers and delivering information to students. In the second perspective, AI facilitated students in collecting information by enabling interactions with messages or peers. In the third perspective, the significance of the automatic evaluation function, which assessed learning activities and provided feedback to enhance the system while simultaneously implementing immediate changes in the learning process, was acknowledged. Regarding the role of communication, teachers clearly intended for students to acquire knowledge through it. Despite the focus on assisting individual learners, each article encompassed references from a wide range of fields and exhibited substantial diversity overall. Consequently, the domain of discussion forums with AI was depicted through the complex interplay between technology, pedagogy, and the learning environment. This context is known as entangled pedagogies, which emphasize understanding the interconnections among these elements and their reciprocal influences. In summary, AI was predominantly utilized in the form of chatbots and GenAI in discussion forums. Emerging AI roles included virtual teachers, peer/message matching, and automated evaluation. Aggregated information was presented in a manner that supported student learning. AI also served as a conduit between students and teachers.

Dynamical downscaling is an essential approach for bridging the gap between coarse-resolution global climate models and regional details required for climate impact assessment and sustainable development planning. Thailand, a climate-sensitive country in Southeast Asia, requires robust climate information to support its adaptation and resilience strategies. This study evaluated the Weather Research and Forecasting (WRF) model in dynamically downscaling selected Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations over Thailand during the baseline period of 1976–2005. A two-way nested WRF configuration was employed, with domains covering Southeast Asia (36 km) and Thailand (12 km) in the model. Model outputs were compared with gridded observations from the Climatic Research Unit (CRU TS), and spatial variations were analyzed across six administrative regions in Thailand. The WRF successfully reproduces broad climatological patterns, including the precipitation contrast between mountainous and lowland areas and the north–south gradient of temperature. Seasonal cycles of rainfall and temperature are generally well represented, although systematic biases remain, specifically the overestimation of orographic rainfall and a cold bias in high-elevation regions. The 12 km WRF simulations demonstrated improved special and temporal agreement with the CRU TS dataset, showing a national-scale wet bias (MBE = +17.14 mm/month), especially during the summer monsoon (+65.22 mm/month). Temperature simulations exhibited seasonal derivations, with a warm bias in the pre-monsoon season and a cold bias during the cool season, resulting in annual cold biases in both maximum (−1.25 C) and minimum (−0.80 C) temperatures. Despite systematic biases, WRF-CMIP5 downscaled framework provides enhanced regional climate information and valuable insights to support national-to-local climate change adaptation, resilience planning, and sustainable development strategies in Thailand and the broader Southeast Asian region.

The initial outbreak of COVID-19 in Thailand in 2020 revealed critical shortages in personal protective equipment (PPE), particularly Powered Air-Purifying Respirators (PAPRs), which are essential for protecting medical personnel from airborne pathogens. This study compared the performance of domestically manufactured PAPRs in Thailand (MM and PP) to two commercially imported models (TM and SM), both of which are generally recognized for their compliance with the EN 12941 standard. The study involved 20 subjects, comprised of 10 males and 10 females, to evaluate three key parameters: total inward leakage (TIL), air supply, and breathing resistance. To replicate real-world conditions, subjects wore ASTM-certified surgical masks beneath the PAPR during the TIL tests. The TIL test employed sodium chloride particles produced by an atomizer and was carried out in a sealed chamber. A scanning mobility particle sizer and laser photometer were used to monitor the concentrations of particles both within and outside the respirator. Leakage under dynamic situations was evaluated using standardized exercises following EN 12941 guidelines. Air supply and breathing resistance were tested with a Sheffield dummy head following international protocols. All PAPRs achieved %TIL values below the 1% EN 12941 threshold, with the TM model having the lowest leakage (0.097%). Domestically produced models performed similarly, with small variations in the PP model due to its PTFE membrane filter. Airflow rates exceeded the design specifications while breathing resistance remained within acceptable limits. Compared to a previous study utilizing dummy head testing, this research demonstrated improved consistency in %TIL results by employing human subjects, emphasizing the importance of real-world testing conditions. Furthermore, the present study highlights the potential of domestically manufactured PAPRs to serve as viable, cost-effective alternatives to imported models. Thai-manufactured PAPRs may improve national resilience in future public health emergencies while lowering reliance on global supply chains if they comply with rigorous testing requirements and demonstrate equivalent protective effectiveness.

Although poly(3-hexylthiophene-2,5-diyl) (P3HT) with its stability-boosting hydrophobic surface is a promising low-cost alternative dopant-free hole transport material for n-i-p perovskite solar cells (PSCs), the P3HT-based PSCs suffer from surface energy mismatch between hydrophilic perovskite and hydrophobic P3HT, which results in interlayer gap, poor electronic contact, and poor charge extraction. In this study, low-cost ferrocene (Fc) acts as an interlayer at the perovskite/P3HT interface, inducing the replacement of the hydrophobic edge-on stacking of alkyl side chains with the hydrophilic π–π stacking of thiophene rings within the P3HT structure to mitigate such an energy mismatch. With an optimal amount of Fc, an average PCE of 23.6% has been achieved under indoor light at 1000 lux in comparison to 20.6% of P3HT-based PSCs without Fc. In addition, an unencapsulated device with the interlayer can retain 80% of initial PCE (T80) over 12 months in the dark with 70% RH, longer than T80 of 8 months without Fc. Finally, a Bluetooth sensor module is powered by three Fc-passivated P3HT-based PSCs connected in series to demonstrate the capacity of replacing batteries used for the Internet of Things (IoTs).

This book is focused on what technical concepts and calculation-based approaches are required to improve and maintain operational excellence. The types of problems that are envisioned are either chronic operating problems or operating problems for which the problem solver has no experience-based solution. While the book discusses the setting of operating metrics and finding hidden problems, the main focus is a problem-solving technique for maintaining plant operational excellence along with real life examples. The book contains examples of application of the five-step approach to process plants and process equipment, development of working hypotheses, and verification of plant instrument data. It deals with solutions to problems where a previous analysis has confirmed a need for new equipment or enhanced operating procedures. The book also deals with simulation tools and the building of “digital twins” to simulate plant operations.

Debottlenecking is defined as increasing capacity by eliminating limitations in the process with a minimal amount of investment. It has sometimes been referred to as “brownfield” investment as opposed to “greenfield” investment. A comprehensive hydraulic review is a critical part of a successful revamp of any plants in chemical process industry—to ensure the process fluid can smoothly move from one place to another. Deep down, the plant owner was aware that the Engineering Procurement and Construction (EPC) contractor conflicted with the industrial best practices. In principle, the plant was still under the EPC contractor's account until the completion of commissioning. Contractually, the plant owner could only comment/review but had no legal right to intervene during the commissioning. While this dilemma is understandable, the plant owner probably should have been more aggressive at an earlier point as abnormal operating techniques were observed.

This chapter deals with applying novel approaches to plant problem-solving. To solve plant problems effectively, we need to be flexible and creative to apply different approaches to the same problem. There were so many times where the author could solve difficult chronic problems of a new never-experienced process after only a few weeks or a few months of learning about the problem, while experts or plant people who had been directly involved in that plant operations for so many years and were supposedly very familiar with the plant could not solve that chronic problem for years. Another important tip to double or triple the success rate of problem-solving is to not jump to the conclusion that the equipment itself is always the root cause of the problem. Maintenance problems may not be so obvious when there is already a potential solution on the table.