Search Results (160)

Urban water supply systems require considerable electrical energy inputs across all operational processes: raw water abstraction, treatment, transmission, and distribution. Consequently, water loss within these processes represents not merely a loss of water volume, but also additional energy consumption and an increase in carbon emissions, given that electricity generation relies predominantly on fossil fuels. This study applied two methodological approaches to analyze the role of water loss within the Water–Energy–Carbon (WEC) Nexus of the Metropolitan Waterworks Authority (MWA), Thailand, over the period 2017–2024. The first method utilized a detailed WEC linkage analysis to balance water inputs and outputs in each process to quantify specific losses: raw water, in-plant, transmission, and distribution losses. The second method applied the International Water Association’s Leakage Emissions Initiative framework, focusing specifically on potable real water loss in distribution process, which constituted the largest volume (64.85% of total losses) and embodied the highest specific energy consumption. Based on the first method, the average annual potable real water loss was 534.71 MCM/yr (23.58% of water supplied to distribution), corresponding to embedded energy and carbon emissions of 103.76 GWh/yr (24.89% of total energy consumption) and 49,562 tCO₂e/yr (24.89% of total carbon emission), respectively. Although the second method was considerably simplified, the estimated energy and carbon emission values were only slightly higher than those derived from the detailed method, demonstrating the second method’s effectiveness as a streamlined assessment tool. These findings underscored that water loss reduction initiatives are essential for minimizing energy consumption and carbon emissions, thereby supporting Thailand’s pathway toward Net Zero emissions by 2050. Full article

The objective of this study was to develop a predictive methodology for assessing the leakage phenomenon of gelatin-based soft capsules under various storage conditions. The equilibrium moisture content of the soft capsules was influenced by the temperature and humidity. The leakage phenomenon was attributable to the swelling of gelatin, as revealed by Fourier Transform Infrared spectroscopy (FT-IR) and Scanning Electron Microscopy (SEM) imaging techniques. Additionally, the moisture diffusion mechanism of soft capsule shells was systematically investigated based on the principles of hygroscopic kinetics, enabling quantitative evaluation of their hygroscopic performance under different environmental conditions. Based on macromechanical analysis, the mechanical failure curves of soft capsule shells under different environmental conditions were investigated, enabling successful determination of the shelf life of the soft capsules. Importantly, the Arrhenius equation and the generalized Eyring model were introduced to successfully predict the occurrence of leakage during storage. The developed prediction method performs successful and accurate stability assessment under various conditions, which is crucial for the development of soft capsules. Full article

Cultivated meat emerges as a promising alternative to conventional meat, the production of which causes significant environmental pressure, including greenhouse gas emissions, water demand, and pasture expansion, alongside ethical concerns related to animal slaughter. Life Cycle Assessments (LCAs) often highlight reductions in these impacts for cultivated meat, but they typically adopt a technocentric perspective, omitting flows of renewable natural resources and human labor. In this context, emergy (with an “m”) environmental accounting offers a valuable methodological complement to LCA, incorporating biophysical and systemic perspectives for a more holistic analysis. The objective of this study is to apply emergy accounting to a cultivated meat production system. The results indicate that cultivated meat exhibits a Unit Emergy Value (UEV) of 0.43 × 10¹³ sej/kg-meat, which is up to 13 times lower than that of conventional meat, thereby indicating a higher emergy efficiency. However, it still depends heavily on economic resources (71.1% of the total emergy). As a result, it presents low emergy yield (EYR of 1.41), high environmental load (ELR of 6.97), low renewability (12.5%), and an emergy sustainability index (ESI) of 0.20 (ESI < 1 denotes unsustainability), thus indicating that the system is unsustainable at its current technological stage. Compared to conventional livestock systems, particularly extensive systems with greater integration of natural resources, cultivated meat presents one of the poorest emergy performances due to its highly artificial energy and material basis, which is dependent on non-renewable resource inputs. These findings contrast with the optimistic conclusions from LCA studies, emphasizing the inferiority of cultivated meat in emergy terms and the need for complementary approaches to generate broader diagnostics. The analysis also identifies optimization opportunities, such as resource input substitution and the integration of renewables, aiming for greater sustainability in protein production. Full article

We present hybrid quantum–classical algorithms to compute time-dependent Møller wavepacket correlation functions via digital quantum simulation. Reactant and product channel wavepackets are encoded as qubit states, evolved under a discretized molecular Hamiltonian, and their correlation is reconstructed using both a modified Hadamard test and a multi-fidelity estimation (MFE) protocol. The method is applied to the collinear H + H₂ exchange reaction on a London–Eyring–Polanyi–Sato potential energy surface. Quantum-estimated correlation functions show quantitative agreement with high-resolution classical wavepacket simulations across the full time domain, reproducing both short-time scattering peaks and long-time oscillatory dynamics. The ancilla-free MFE protocol achieves matching results with reduced circuit depth. These results provide a proof of principle that digital quantum circuits can be used to accurately calculate the wavepacket correlation functions for a benchmark chemical reaction system. Full article

This study optimizes fertilization schemes through the emergy analysis of different nutrient reduction treatments in maize cropping ecosystems in Xinjiang, thereby providing technical support for improving chemical fertilizer use efficiency and maintaining the stability of farmland ecosystems. The study was conducted in 2024 at Huaxing Farm in Changji Hui Autonomous Prefecture, Xinjiang Uyghur Autonomous Region. The experiment used the local conventional nitrogen and phosphorus fertilization rates as the control treatment N0P0 (applying P 183 kg·hm⁻² and N 246 kg·hm⁻²), with eight different N and P nutrient reduction treatments: N0P1 (10% reduction in P only), N0P2 (20% reduction in P only), N1P0 (10% reduction in N only), N2P0 (20% N reduction), N1P1 (10% N and P reduction), N1P2 (10% N and 20% P reduction), N2P1 (20% N and 10% P reduction), and N2P2 (20% N and P reduction). Each treatment was replicated three times. Based on biomass data of maize plant components under different fertilization treatments, emergy analysis of farmland ecosystems and integration of economic benefit indicators led to the optimization of an optimal fertilization scheme. Results indicate that the N0P1 treatment performed optimally: maize plant biomass reached 251.09 g, significantly higher than other treatments. The N0P1 treatment exhibited the highest energy output (3.23 × 10¹⁶ sej·hm⁻²), the highest net energy yield ratio (EYR) of 1.45, and an energy sustainability index (ESI) of 3.34, representing a high level. It also delivered the highest economic benefit, with a net profit of 8571.95 CNY·hm⁻² and a production–investment ratio of 1.71. In conclusion, the N0P1 treatment (10% reduction in phosphorus alone) demonstrated superior performance in biomass yield, energy utilization efficiency, ecological sustainability, and economic benefits, making it the optimal fertilization strategy for maize fields in this region. Full article

An experimental and theoretical investigation of the reaction between chlorine atoms and propane/deuterated propane (C₃H₈/C₃D₈) was performed. The experimental work aimed to determine absolute and site-specific rate constants for hydrogen and deuterium abstraction in the Cl + C₃H₈/C₃D₈ system. Measurements were conducted using the relative rate method at three temperatures between 298 and 387 K. Total rate constants for H/D abstraction by chlorine, as well as individual rate constants for abstraction from primary and secondary carbon sites, were obtained. The kinetic data for H abstraction agree well with previously reported literature values, confirming the reliability of the experimental approach. Notably, rate constants for the C₃D₈ + Cl reaction were determined for the first time, and the consistency of these results supports the reliability of the newly derived kinetic parameters. In the theoretical part of the study, hydrogen/deuterium abstraction from propane by atomic chlorine was analyzed within an atmospheric-chemistry context to clarify temperature dependence and site selectivity. Stationary points (SC, TS, PC, reactants, products) were optimized at MP2/aug-cc-pVDZ and verified by harmonic frequencies and intrinsic reaction-coordinate analyses. Eyring transition-state theory yielded 298–550 K rate constants with activation free energies referenced to SC. Our calculations indicate entrance-channel complex formation and effectively barrierless progress for most pathways; a small barrier appears only for RD1′. L-parameter evaluation classifies TS2 as reactant-like, and branching ratios identify –CH₂– abstraction (RX2) as dominant. These findings align with the experimental data. Full article

This study examined the influence of brand presence and discrete emotions on consumer acceptance and purchase intent of commercial chicken noodle soups. A total of 324 evaluations across three soup categories (chunky, low-sodium, condensed) were conducted under blind and unblinded conditions using a 42-term emotion lexicon. Brand presence did not exert moderate-to-large effects, though subtle brand-specific differences cannot be excluded. Instead, three emotions, “satisfied,” “disgusted,” and, for condensed soups, “bored,” emerged as the strongest predictors, together explaining a substantial proportion of variance in liking and purchase intent. Many other positive emotions clustered around “satisfied,” highlighting a parsimonious set of dominant drivers. Quiet positive emotions such as contentment, peacefulness, and warmth consistently aligned with both acceptance and purchase intent. These findings extend prior research by showing that consumer responses consolidate around a limited set of emotions, underscoring that evoking subtle, self-focused positive feelings may be more effective in comfort food marketing and product development than reliance on brand identity or nostalgia. Full article

Nanotechnology has become a transformative field in modern science and engineering, offering innovative approaches to enhance conventional thermal and fluid systems. Heat and mass transfer phenomena, particularly fluid motion across various geometries, play a crucial role in industrial and engineering processes. The inclusion of nanoparticles in base fluids significantly improves thermal conductivity and enables advanced phase-change technologies. The current work examines Powell–Eyring nanofluid’s heat transmission properties on a stretched Riga plate, considering the effects of magnetic fields, porosity, Darcy–Forchheimer flow, thermal radiation, and activation energy. Using the proper similarity transformations, the pertinent governing boundary-layer equations are converted into a set of ordinary differential equations (ODEs), which are then solved using the boundary value problem fourth-order collocation (BVP4C) technique in the MATLAB program. Tables and graphs are used to display the outcomes. Due to their significance in the industrial domain, the Nusselt number and skin friction are also evaluated. The velocity of the nanofluid is shown to decline with a boost in the Hartmann number, porosity, and Darcy–Forchheimer parameter values. Moreover, its energy curves are increased by boosting the values of thermal radiation and the Biot number. A stronger Hartmann number M decelerates the flow (thickening the momentum boundary layer), whereas increasing the Riga forcing parameter Q can locally enhance the near-wall velocity due to wall-parallel Lorentz forcing. Visual comparisons and numerical simulations are used to validate the results, confirming the durability and reliability of the suggested approach. By using a systematic design technique that includes training, testing, and validation, the fluid dynamics problem is solved. The model’s performance and generalization across many circumstances are assessed. In this work, an artificial neural network (ANN) architecture comprising two hidden layers is employed. The model is trained with the Levenberg–Marquardt scheme on reliable numerical datasets, enabling enhanced prediction capability and computational efficiency. The ANN demonstrates exceptional accuracy, with regression coefficients $R\approx 1.0$ and the best validation mean squared errors of $8.52\times {10}^{-10}$, $7.91\times {10}^{-9}$, and $1.59\times {10}^{-8}$ for the Powell–Eyring, heat radiation, and thermophoresis models, respectively. The ANN-predicted velocity, temperature, and concentration profiles show good agreement with numerical findings, with only minor differences in insignificant areas, establishing the ANN as a credible surrogate for quick parametric assessment and refinement in magnetohydrodynamic (MHD) nanofluid heat transfer systems. Full article

Sustainable intensification requires metrics that are able to capture both economic performance and the often-hidden environmental inputs that support agriculture. Emergy analysis (EmA) meets this need by converting all inputs—free environmental flows and purchased goods/services—into a common unit (solar emjoules, sej). We conducted a PRISMA-documented bibliometric review of EmA in agroecosystems (Web of Science + Scopus, 2000–2022) using Bibliometrix and synthesized farm-scale indicators (ELR, EYR, ESI, %R). Our results show output has grown but is concentrated in a few countries (China, Italy and Brazil) and journals, with farm-level assessments dominating over regional and national assessments. Across cases, mixed crop–livestock systems tend to show lower environmental loading (ELR) and higher sustainability (ESI) than crop-only or livestock-only systems. %R is generally modest, indicating continued reliance on non-renewables, with fertilizers (crops) and purchased feed (livestock) identified as recurrent drivers. Thematic mapping reveals well-developed niche clusters but no single motor theme, consistent with the presence of incongruous baselines, transformities and boundaries that limit comparability. We recommend adoption of the 12.1 × 10²⁴ sej yr⁻¹ baseline, transparent transformity reporting and multi-scale designs that link farm diagnostics to basin and national trajectories. Co-reporting with complementary sustainability assessment methods (such as LCA and carbon footprint), along with appropriate UEV resources, would increase its reputation among policymakers while preserving EmA’s systems perspective, converting dispersed case evidence into cumulative knowledge for circular, resilient agroecosystems. Full article

Accurately modelling and simulating the stiffness modulus of asphalt mixtures is essential for reliable pavement design and performance prediction under varying environmental and loading conditions. The preceding is commonly achieved through master curves, which relate stiffness to loading frequency at a reference temperature. However, conventional master curves face two primary limitations. Firstly, temperature is not treated as a state variable; instead, its effect is indirectly considered through shift factors, which can introduce inaccuracies due to their lack of thermodynamic consistency across the entire range of possible temperatures. Secondly, conventional master curves often encounter convergence difficulties when calibrated with experimental data constrained to a narrow frequency spectrum. In order to address these shortcomings, this investigation proposes a novel formulation known as the Thermo-Stiffness Integration (TSI) model, which explicitly incorporates both temperature and frequency as state variables to predict the stiffness modulus directly, without relying on supplementary expressions such as shift factors. The TSI model is built on thermodynamics-based principles (such as Eyring’s rate theory and activation free energy) and leverages the time–temperature superposition principle to create a physically consistent representation of the mechanical behaviour of asphalt mixtures. This manuscript presents the development of the TSI model along with its application in a case study involving eight asphalt mixtures, including four hot-mix asphalts and four warm-mix asphalts. Each type of mixture contains recycled concrete aggregates at replacement levels of 0%, 15%, 30%, and 45% as partial substitutes for coarse natural aggregates. This diverse set of materials enables a robust evaluation of the model’s performance, even under non-traditional mixture designs. For this case study, the TSI model enhances computational stability by approximately 4 to 45 times compared to conventional master curves. Thus, the main contribution of this research lies in establishing a valuable mathematical tool for both scientists and practitioners aiming to improve the design and performance assessment of asphalt mixtures in a more physically realistic and computationally stable approach. Full article

Epoxy adhesives derived from bisphenol A diglycidyl ether (BADGE) are widely utilized in segmental construction—particularly in precast concrete structures—and in building structural strengthening, owing to their outstanding adhesion properties and long-term durability. These materials constitute a significant class of polymeric adhesives in structural engineering applications. However, BADGE-based epoxy adhesives are susceptible to aging under service conditions, primarily due to environmental stressors such as thermal cycling, oxygen exposure, moisture ingress, ultraviolet radiation, and interaction with corrosive media. These aging processes lead to irreversible physicochemical changes, manifested as degradation of microstructure, mechanical properties, and dynamic mechanical properties to varying degrees, with performance deterioration becoming increasingly significant over time. Notably, for the mechanical properties of concern, the decline can exceed 40% in accelerated aging tests. A comprehensive understanding of the aging behavior of BADGE-based epoxy resin under realistic environmental conditions is essential for predicting long-term performance and ensuring structural safety. This paper provides a critical review of existing studies on the aging behavior of BADGE-based epoxy resins. This paper summarizes the findings of various aging tests involving different influencing factors, identifies the main degradation mechanisms, and evaluates current methods for predicting long-term durability (such as the Arrhenius method, Eyring model, etc.). Furthermore, this review provides recommendations for future research, including investigating multifactorial aging, conducting natural exposure tests, and establishing correlations between laboratory-based accelerated aging and field-exposed conditions. These recommendations aim to advance the understanding of long-term aging mechanisms and enhance the reliability of BADGE-based epoxy resins in structural applications. Full article

The electroosmotic flow (EOF) of non-Newtonian fluids plays a significant role in microfluidic systems. The EOF of Powell–Eyring fluid within a parallel-plate microchannel, under the influence of both electric field and pressure gradient, is investigated. Navier’s boundary condition is adopted. The velocity distribution’s approximate solution is derived via the homotopy perturbation technique (HPM). Optimized initial guesses enable accurate second-order approximations, dramatically lowering computational complexity. The numerical solution is acquired via the modified spectral local linearization method (SLLM), exhibiting both high accuracy and computational efficiency. Visualizations reveal how the pressure gradient/electric field, the electric double layer (EDL) width, and slip length affect velocity. The ratio of pressure gradient to electric field exhibits a nonlinear modulating effect on the velocity. The EDL is a nanoscale charge layer at solid–liquid interfaces. A thinner EDL thickness diminishes the slip flow phenomenon. The shear-thinning characteristics of the Powell–Eyring fluid are particularly pronounced in the central region under high pressure gradients and in the boundary layer region when wall slip is present. These findings establish a theoretical base for the development of microfluidic devices and the improvement of pharmaceutical carrier strategies. Full article

Viscous properties play a major role in the time-dependent deformation behavior of polymers and have long been characterized using spring-dashpot models. However, such models face a bottleneck of having multiple sets of model parameter values that can all be used to simulate the same deformation behavior. As a result, these model parameters have not been widely used to quantify the viscous properties. In this study, a newly developed multi-relaxation-recovery test was used to obtain the variation in stress response to deformation of polyethylene (PE) and its pipes during relaxation, revealing the complexity of PE’s nonlinear viscous stress response to deformation. Using a three-branch spring-dashpot model with two Eyring’s dashpots, this study shows the possibility of determining the model parameter values using four different analysis methods, namely, the mode method, peak-point method, highest-frequency method, and best-five-fits method. Model parameter values from these methods are compared and discussed in this paper, to reach the conclusion that the best-five-fits method provides the most reliable and relatively unique set of model parameter values for characterizing the mechanical performance of PE and its pipes. The best-five-fits method is expected to enable the use of the model parameters to quantify PE’s viscous properties so that PE’s load-carrying performance can be properly characterized, even for long-term applications. Full article

This work aims to explore the magnetohydrodynamic mixed convection boundary layer flow (MHD-MCBLF) on a slanted extending cylinder using Eyring–Powell fluid in combination with Levenberg–Marquardt algorithm–artificial neural networks (LMA-ANNs). The thermal properties include thermal stratification, which has a higher temperature surface on the cylinder than on the surrounding fluid. The mathematical model incorporates essential factors involving mixed conventions, thermal layers, heat absorption/generation, geometry curvature, fluid properties, magnetic field intensity, and Prandtl number. Partial differential equations govern the process and are transformed into coupled nonlinear ordinary differential equations with proper changes of variables. Datasets are generated for two cases: a flat plate (zero curving) and a cylinder (non-zero curving). The applicability of the LMA-ANN solver is presented by solving the MHD-MCBLF problem using regression analysis, mean squared error evaluation, histograms, and gradient analysis. It presents an affordable computational tool for predicting multicomponent reactive and non-reactive thermofluid phase interactions. This study introduces an application of Levenberg–Marquardt algorithm-based artificial neural networks (LMA-ANNs) to solve complex magnetohydrodynamic mixed convection boundary layer flows of Eyring–Powell fluids over inclined stretching cylinders. This approach efficiently approximates solutions to the transformed nonlinear differential equations, demonstrating high accuracy and reduced computational effort. Such advancements are particularly beneficial in industries like polymer processing, biomedical engineering, and thermal management systems, where modeling non-Newtonian fluid behaviors is crucial. Full article

Fractional differential viscoelastic calculus was used to develop a model for predicting the primary to tertiary creep in the tensile creep deformation of various polypropylenes (PPs). The primary and secondary creep were described via simple fractional differential viscoelasticity with an empirical formula for the stress and temperature dependence of the fractional differential order. Tertiary creep was treated as a pure viscous body with damage. The temperature dependence is treated simply, and Arrhenius’s law is applied. As for stress dependence, the Eyring law of the sinh function was applied to the primary and secondary creep processes, while the WLF-type shift function was adopted for tertiary creep. The primary and secondary creep behaviors of each model material showed creep growth rates according to the rigidity of each material. As for the tertiary creep, the homo PP showed a little damage progression with a damage index of 0.17, while the impact-resistant PP showed faster damage progression with a damage index of around 0.5. The three types of post-consumer recycled PPs showed intermediate properties between these virgin PPs, and no peculiarities were confirmed in the static creep behaviors. It was confirmed that the creep experimental results for all model materials fell on the same Monkman–Grant law. The presented creep model can predict the creep strain transition and minimum strain rate well and is effective in predicting the creep characteristics of PPs. Full article