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Energy-Saving HVAC System and Design Methods Utilizing Medium-Temperature Chilled Water for Office Buildings
No full textThis paper presents an energy-saving HVAC system and design method using medium- temperature chilled water for office buildings. The proposed heat load calculation method focuses only on necessary areas, reducing air volume load compared to conventional methods. It separates heat load calculations for interior and ceiling spaces. The air volume is calculated based on the interior load, while the ceiling space load—mainly from lighting and skin load—is included in coil load but excluded from air volume load. Typically, air cooling uses chilled water at around 7°C. This system adopts a two-step cooling process using medium-temperature chilled water and chilled water to increase chiller outlet temperature and improve efficiency by approximately 25%. Outside or return air is first pre-cooled with medium-temperature chilled water, then cooled further to the required temperature. In this system, outside air is cooled to 16°C and supply air to 12°C. About 50% of the total heat load can be handled by medium-temperature chilled water, allowing the chiller to operate at a higher outlet temperature and achieve greater efficiency
A cold storage air conditioning system with energy-efficient supercooled water ice slurry generation by using heat recovery and regeneration
No full textIce slurry cold storage technology using supercooled water is considered one of the most efficient methods. In traditional systems, to prevent ice crystal blockage in the supercooled water exchanger, the water from ice tank is typically heated to 0.5°C to melt ice crystals , resulting in a 15%–20 % cooling loss and a potential blockage risk. Although heat regeneration method has been introduced to mitigate cooling loss, the internal heat-cold offset still limits system efficiency. In this study, a novel system integrating both heat recovery and heat regeneration is proposed to improve system efficiency. In the system, return chilled water is used to melt ice crystals, enabling cooling energy recovery and eliminating the heat-cold offset, while the regeneration exchanger is used to decrease the inlet temperature of the supercooled water exchanger, reducing the cooling loss. A mathematical model of the whole system is developed and the system performance under rated operating condition is analyzed. The results indicate the proposed system enhances ice-crystal melting, increases the effective utilization of cooling capacity by 7.14 %, and improves the ice-making COP by 6.1% compared with the traditional system, and increases the system COP by 18.3% and 12.2% compared with the traditional and regeneration systems, respectively
Comparative study of different control strategies for radiant ceiling panel system
No full textRadiant ceiling panel (RCP) system has been increasingly adopted in recent years. However, its optimal control strategies have yet to be established. In previous studies, a grey-box model has been developed to predict the indoor thermal condition when using a RCP system. Based on this model, a control framework was implemented in MATLAB/Simulink, in which the inlet water temperature was regulated by a controller to maintain the indoor air temperature at a setpoint of 20 ℃. Different sampling period (1 min,10 min, 30 min and 1hour) were investigated with respect to system accuracy. Three control strategies- on off control, PID control, and model predictive control (MPC) were evaluated in terms of their performance on indoor temperature control and energy consumption reduction. For PID control, the gains were tuned by Ziegler–Nichols tuning method, and performance comparisons were made among P control, PI control and PID control. The results show that both PID control and MPC can effectively maintain the indoor temperature at the setpoint while consuming less energy consumption compared to on off control. In particular, MPC outperformed PID control by exhibiting fewer temperature fluctuations, owing to its ability to optimize control actions based on future state predictions
A large language model-based framework with retrieval-augmented generation for automated building energy modeling
No full textBuilding energy models (BEMs) are crucial for design and analysis but often require considerable time and expertise due to reliance on specialized software and manual configuration. To address these challenges, this study proposes a framework based on large language model (LLM) with retrieval-augmented generation for automating building energy modeling. The proposed framework leverages the advanced natural language processing capabilities of LLM to parse user inputs expressed in natural language. Historical BEMs that match these requirements are retrieved from a feature database, providing reference data to the LLM to enhance the accuracy and adaptability of the generated results. This approach enables the rapid construction of BEMs tailored to user specifications. Experimental results demonstrate that the modeling time is reduced from several hours, which is typical of traditional manual methods, to just a few minutes, resulting in a significant improvement in efficiency. Furthermore, the accuracy of the load simulations is highly consistent with the results from manual modeling, confirming the reliability of this method in real-world applications. This framework offers an efficient and intelligent solution for building energy analysis and simulation, highlighting the substantial potential of large language model in advancing building simulation and performance modeling
Computational Analysis of the Radical Scavenging Activity of Polyketide Present in Talaromyces Funiculosus
No full textPolyketides such as Talafun (TF) and N-(4-hydroxy-2-methoxyphenyl) acetamide (AM), derived from Talaromyces funiculosus, are promising bioactive molecules exhibiting antioxidant, antimicrobial, anti-inflammatory, and anticancer activities. In response to the increasing prevalence of oxidative stress-related disorders, this study investigates the antioxidant potential of these compounds using Density Functional Theory (DFT), molecular docking, and ADMET profiling. Radical scavenging mechanisms were explored in both gas and aqueous phases, focusing on Hydrogen Atom Transfer (HAT), Single Electron Transfer-Proton Transfer (SET-PT), and Sequential Proton Loss Electron Transfer (SPLET). The results suggest that AM exhibits higher radical scavenging activity through the HAT mechanism, whereas TF demonstrated superior xanthine oxidase (XO) inhibition. Both ligands showed favorable pharmacokinetic properties, indicating therapeutic potential. This work provides molecular-level insights into their reactivity, stability, and applicability as antioxidant agents
Analytical solution of a free-fermion chain with time-dependent ramps
No full textWe provide an exact analytical solution of the single-particle Schrödinger equation for a chain of non-interacting fermions subject to a time-dependent linear potential, with its slope varied as an arbitrary function of time. The resulting dynamics exhibit self-similar behavior, with a structure reminiscent of the domain wall melting problem, albeit characterized by a nontrivial time-dependent length scale and phase. Building on this solution, we derive hydrodynamic predictions for the evolution of particle density, current, and entanglement entropy along the chain. In the special case of a sudden quench, the system develops a breathing interface region, which may be interpreted as a realization of Wannier-Stark localization, as previously suggested on the basis of hydrodynamic arguments
Bosonic string theories in non-commutative space-time with deformed dispersion relations
No full textIn this paper, we study string theories with deformed commutation relations and ordinary constraints to derive the Magueijo-Smolin form of deformed relativistic dispersion relations. A closed energy-dependent constraints algebra is obtained. We quantize these theories, and we find that the characteristics of the spectrum change with respect to the total energy functions. This deformation is equivalent to work in an energy- and mass-dependent potential. In a particular choice of the energy-dependent functions, the tachyonic state can be eliminated and the next excited states accumulate below the Planck scale
Probiotic Interventions in Antibiotic-Associated Diarrhea: Mechanistic Insights, Therapeutic Efficacy, and Emerging Nanotechnological Formulations
No full textAntibiotic-associated diarrhea (AAD) is a common adverse effect of antibiotic therapy, primarily resulting from gut microbiota disruption. Probiotics have emerged as promising agents to restore intestinal microbial balance and support gastrointestinal health, yet uncertainties remain regarding their mechanisms, strain-specific efficacy, and clinical optimization. This review evaluates the role of probiotics in the prevention and management of AAD, analyzes their clinical efficacy, and explores microbial insights to guide future probiotic interventions. A systematic review of randomized controlled trials, meta-analyses, and microbiome-based studies was performed. Key parameters, including probiotic strain specificity, dosage, treatment duration, and safety, were assessed through data synthesis from clinical and microbiome analyses. Probiotics were found to restore gut microbial diversity, strengthen mucosal barrier function, and modulate immune responses. Evidence supports that Lactobacillus rhamnosus GG and Saccharomyces boulardii effectively reduce the incidence of AAD. Emerging approaches involving personalized probiotic therapy based on individual microbiota profiles demonstrate potential benefits, though heterogeneity in trial design and formulations remains a challenge. Probiotics represent an effective adjunct in AAD prevention and management. Future research should prioritize strain-specific, personalized clinical trials and develop standardized guidelines incorporating microbiome profiling to optimize probiotic selection and therapeutic outcomes
Observability and unique continuation inequalities for the Schr\"{o}dinger equations with inverse-square potentials
No full textIn this paper, we focus on the Schr\"{o}dinger equations with inverse-square potentials in dimension one; these special potentials play an important role in the field of mathematical physics. We study several observability and unique continuation inequalities at one time point or at two time points for these equations. These observability and unique continuation inequalities are some new types of quantitative estimates which have appeared in recent literature. Their proofs essentially rely on the representation of the solution, a Nazarov-type uncertainty principle for the Hankel transform, and an interpolation inequality for functions whose Hankel transforms have compact support. Meanwhile, these inequalities can be applied to the controllability of these Schr\"{o}dinger equations
Performance Analysis of Ternary Biomass-Coal Co-Firing Using Integrated TGA-CFD Modeling
No full textCo-firing multiple biomass types in coal-fired power plants presents complex analytical challenges that require a detailed understanding of fuel interactions and emission behaviors. Existing single-fuel methods are insufficient for predicting synergistic effects in ternary biomass-coal mixtures, necessitating the use of integrated experimental and computational strategies to optimize industrial-scale emissions. This study aimed to evaluate the performance of multi-biomass co-firing through combined thermogravimetric analysis (TGA) and computational fluid dynamics (CFD) modeling, measuring synergistic interactions and emission reduction potential in large-scale coal-fired boilers. Three multi-biomass mixtures were systematically analyzed: Mixture A (50% coal + 25% sawdust + 25% rice husk), Mixture B (50% coal + 25% rice husk + 25% SRF), and Mixture C (50% coal + 25% sawdust + 25% SRF). TGA experiments were conducted at heating rates of 10-40°C/min under oxygen and air atmospheres, while CFD simulations used a validated 600 MW Class CFPP (Coal Fired Power Plant) boiler model with 950,000 hexahedral elements and Rosin-Rammler particle distribution modeling. Beyond combustion efficiency, this research extends to sensitivity analysis of biomass ratios, economic feasibility, and long-term operational impacts such as fouling and erosion. TGA analysis showed strong synergistic effects with Mixture A, reaching the highest comprehensive combustion index (4.67) and peak reaction rate (13.08%/min), which was a 282% increase over the baseline coal. CFD simulations indicated significant emission reductions: CO₂ was lowered by 45.7% (Mixture C), SO₂ by 67.14% (Mixture A), and NOₓ by 30.71% (Mixture A). Model validation confirmed high accuracy, with only 3.59% error in O₂ concentration and 1.63% error in outlet temperature. The power derating ranged from 21.67% to 28.33%, with Mixture C exhibiting the best overall performance. The integrated TGA-CFD approach effectively quantifies multi-biomass synergistic interactions and emission reduction potential, providing critical insights for sustainable coal power operations and Indonesia's Net Zero Emissions 2060 goal